Clear Cell Renal Cell Carcinoma Biomarkers

ABSTRACT

Disclosed herein is a clear cell renal cell carcinoma (ccRCC) biomarker set. Also disclosed herein is a detection system using the biomarker set disclosed herein, methods of determining whether a subject has or shows recurrence of clear cell renal cell carcinoma, method of determining whether a renal mass sample is benign or malignant, method of detecting response of a subject to systemic treatment, and a kit for carrying out the same.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of priority of Singapore applicationNo. 10201707218R, filed 5 Sep. 2017, the contents of it being herebyincorporated by reference in its entirety for all purposes.

FIELD OF INVENTION

The present invention relates to molecular biology in particularbiomarkers. In particular, the present invention relates to biomarkersassociated with clear cell renal cell carcinoma (ccRCC) and methods anduses thereof.

BACKGROUND OF THE INVENTION

Renal cell carcinoma (RCC) is one of the most deadly cancers due tofrequent late diagnosis and poor treatment options. Success in curingthe disease relies on early detection of RCC and complete resection ofthe malignant cells. Since the kidney lies deeply in the retroperitonealspace, renal cell carcinoma is primarily asymptomatic in the early phaseand upon diagnosis the tumour is large and/or metastasized. The threemost common subtypes of renal cell carcinoma are clear cell renal cellcarcinoma, papillary renal cell carcinoma and chromophobe renal cellcarcinoma. Clear cell renal cell carcinoma is the most common subtype,accounting for 75-90% of all renal cell carcinomas and with 338,000 newcases in 2012 worldwide.

With most clear cell renal cell carcinomas being resistant tochemotherapy and radiotherapy, patients with metastatic clear cell renalcell carcinomas exhibit a dismal 8% five-year overall survival. Evenearly stage tumours remain at risk of metastatic progression aftersurgery, with 20-40% of patients having recurrence. Therefore,identification of this high-risk group of renal cell carcinoma patientsremains a challenge. Furthermore, different subtypes of renal cellcarcinoma have variable prognoses and treatment response rates.Therefore, it is crucial to be able to differentiate between differentsubtypes of renal cell carcinoma.

Previous methods for diagnosing patients with clear cell renal cellcarcinoma involve invasive methods, including tumour biopsy, or imagingmethods including ultrasound imaging or magnetic resonance imaging.However, based on known methods, it is difficult to determine whether arenal mass of less than 4 cm is a tumour, and/or whether the tumour isbenign or malignant based on imaging studies alone. Around 50% to 60% ofrenal masses are less than 4 cm, of which 25% to 30% are benign tumours.The risk of overtreatment for small renal masses ranges from 40% forlesions less than 1 cm to 17% for masses 3 to 4 cm in diameter. Inaddition to initial diagnosis, the main tools for post-treatment followup or active surveillance also include only imaging studies. Surgery orablation would result in tissue change and scar formation, causing thedetection of local recurrence to be challenging. Lastly, there is also alack of methods to assess the efficiency of systemic treatments inadvanced clear cell renal cell carcinoma patients. In view of the above,there is an unmet need for a method of identifying clear cell renal cellcarcinoma, differentiation of benign lesions from malignant tumours, fordetection of recurrence after local treatments, and for assessment ofsystemic treatments.

SUMMARY OF INVENTION

In one aspect, the present invention refers to a clear cell renal cellcarcinoma (ccRCC) biomarker set, wherein the biomarker set comprises atleast two biomarkers selected from the group consisting of ZNF395,SMPDL3A, SLC28A1, SLC6A3, VEGFA, EGLN3, wherein one of the at least twobiomarkers is SMPDL3A or SLC28A1; wherein the biomarkers are proteins,or nucleic acids encoding the same, or variants thereof.

In another aspect, the present invention refers to a detection systemcomprising a) a receiving section to receive a sample from a subjectsuspected to suffer from clear cell renal cell carcinoma, and whereinthe sample is suspected to comprise the biomarker set as disclosedherein; and b) a detection section comprising a substance or substancescapable of detecting the biomarker set as disclosed herein.

In one aspect, the present invention refers to a method of determiningwhether a subject has or shows recurrence of clear cell renal cellcarcinoma, wherein the method comprises obtaining a sample from thesubject; detecting the presence of the biomarker set as disclosed hereinin the sample using a detection system as disclosed herein, wherein thepresence of the biomarker set determines that the subject has or showsrecurrence of clear cell renal cell carcinoma.

In a further aspect, the present invention refers to a method ofdetecting response of a subject to systemic treatment, the methodcomprising a) obtaining a sample from the subject; and b) determiningthe levels of the biomarker set as defined herein in the sample; whereina decrease in levels or an absence of the biomarker set indicates thatthe subject is responsive to treatment.

In yet another aspect, the present invention refers to a method ofdetermining whether a renal mass sample is benign or malignant, themethod comprising obtaining a sample from the renal mass of a subject;determining the levels or the presence or absence of the biomarker setas disclosed herein in the sample; wherein the increase in levels of thebiomarker set compared to a benign sample indicates that the sample ismalignant.

In another aspect, the present invention refers to a kit for carryingout the method as disclosed herein, wherein the kit comprises adetection buffer, a lysis buffer, and a substance or substances asdefined herein suitable for the detection of the biomarker set asdisclosed herein.

In a further aspect, the present invention refers to a kit as disclosedherein and a detection system as disclosed herein for detecting thebiomarker set as defined herein.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will be better understood with reference to the detaileddescription when considered in conjunction with the non-limitingexamples and the accompanying drawings, in which:

FIG. 1 illustrates that von Hippel-Lindau (VHL) deficient clear cellrenal cell carcinoma tumours exhibit an aberrant cis-regulatorylandscape. FIG. 1A shows a graph that illustrates the percentage ofoverlap of the histone chromatin immunoprecipitation sequencing(ChIP-seq) (H3K27ac, H3K4me3 and H3K4me1) peaks of normal kidney tissueswith peaks from adult kidney tissues in the Epigenomics Roadmap dataset.FIG. 1B shows a graph illustrating the percentage of overlap of histoneChIP-seq (H3K27ac, H3K4me3 and H3K4me1) peaks between five primary clearcell renal cell carcinoma tumours and cell lines derived from thesetumours. FIG. 10 shows a table and a diagram illustrating that theputative active promoters are defined by co-occurrence of H3K4me3,H3K27ac within 2 kilo bases (kb) proximity to transcription start sites(TSS); and putative active enhancers are defined by the presence ofH3K4me1, H3K27ac and the exclusivity with promoters. The table furtherillustrates the total number of identified putative promoters andputative enhancers; and the total number of gained promoters, lostpromoters, gained enhancers and lost enhancers identified in this study.FIG. 1D shows a graph illustrating principal component analysis (PCA)using all 17,497 promoters and 66,448 enhancers to classify normalsamples and tumour samples into distinct clusters. The numbers in thegraph depicts patient IDs which are the following 1-12364284;2-17621953; 3-20431713; 4-40911432; 5-57398667; 6-70528835; 7-74575859;8-77972083; 9-86049102 and 10-75416923. FIG. 1E shows graphsillustrating saturation analysis of the total number of predictedpromoters or enhancers across increasing number of primary samples. Thetotal number of predicted promoters saturates at 4 or more samples whilethe total number of predicted enhancers saturates at 16 or more samples.The dotted line indicates the total number of predicted regulatoryelements by integrating all 10 normal-tumour pairs (n=20). The whiskersindicate standard deviations. FIG. 1F shows graphs and tables describingthe variances captured by each principle component from normalizedH3K27ac signals at promoters or enhancers. The cumulative percentages ofvariance are indicated in the tables. FIG. 1G shows a graph of thenumber of altered promoters and enhancers per patient. FIG. 1H shows agraph of the fraction of altered regions that meet statisticalsignificance defined by paired t-tests with Benjamini-Hochbergcorrection (q value <0.10) at different cut-offs of recurrence. FIG. 1Ishows a graph of the differences in the fractions of regions meetingstatistical significance. Promoters reach saddle point at n 5 whileenhancers reach saddle point at n 6. FIG. 1J shows a heatmap withH3K27ac levels of altered promoters and enhancers in a paired patienttissue (patient 40911432). High signal levels are reflected in white andlow signal levels are reflected in black. FIG. 1Ki and FIG. 1Kii shows aplot referring to examples of H3K27ac chromatin immunoprecipitationsequencing (ChIP-Seq) signals in 10 normal-tumour pairs shown for gainedpromoter, lost promoter, unaltered promoter, gained enhancer, lostenhancer and unaltered enhancer. N refers to signal from normal tissueand T refers to signal from tumour tissue. FIG. 1L shows box plots ofH3K27ac levels, chromatin accessibility and DNA methylation of gainedpromoters and gained enhancers. Gene expression of the nearest clearcell renal cell carcinoma long coding RNA (lncRNA) is compared betweennormal and tumour tissues. ***p-value <0.001, two-sided t-test. FIG. 1Mshows a plot referring to histone ChIP-seq signals (H3K27ac, H3K4me1,H3K4me3), RNA-Seq signals and FAIRE-Seq signals at the CCND1 locus in atumour-normal tissue sample pair of patient 40911432. For comparison,the histone ChIP-seq profiles of normal adult kidney tissue from theEpigenome Roadmap are displayed above the normal tissue profilesgenerated by Nano-ChIP-seq. The histone profile of a cell line derivedfrom tumour tissue is displayed below the profile of the normal tissue.

FIG. 2 shows that enhancer aberration is a signature of clear cell renalcellcarcinoma. FIG. 2A shows bar graphs of enriched pathways associatedwith gained promoters and gained enhancers revealed by GREAT algorithmthat is ranked by binomial FDR q-value. FIG. 2B illustrates a plot thatrefers to a histone chromatin immunoprecipitation sequencing (ChIP-Seq)profile of VEGFA. De novo enhancers are acquired in a clear cell renalcell carcinoma tumour tissue upstream of VEGFA. Capture-C confirmedinteractions of this VEGFA enhancer (E) with its promoter (P) in 786-Ocells. The arcs represent significant interactions detected by r3Cseq(q<0.05). The input-subtracted H3K27ac signals of this enhancer arehighly correlated with VEGFA gene expression (Spearman's correlation).FIG. 2C illustrates a plot that refers to a histone ChIP-Seq profile ofSLC2A1/GLUT1. A de novo tumour enhancer interacts with the SLC2A1/GLUT1promoter. FIG. 2D and FIG. 2E illustrates a plot that refers to ahistone ChIP-Seq profile of (D) PLIN2 and (E) SLC38A1, with gain ofpromoters and enhancers near overexpressed respective clear cell renalcell carcinoma oncogenes PLIN2 and SLC38A1. FIG. 2F shows a graph of thetop 5 gene ontology Molecular Functions of tumour promoters andenhancers. FIG. 2G shows a dot plot referring to Spearman's correlationbetween gene expression of VEGFA and SLC2A1 and the input subtractedH3K27ac levels of their predicted enhancers in 10 tumour samples andtheir matched normals. FIG. 2H shows a graph referring to the cumulativedistribution of distance spanned by significant Capture C interactions.

FIG. 3 illustrates the identification of key oncogenic drivers by tumoursuper-enhancers. FIG. 3A shows a graph referring to a total of 1,451super-enhancers that are identified by ROSE and ranked by theirdifferential H3K27ac intensity between normal and tumour tissues. Genesassociated with the top gained and lost super-enhancers are listed. FIG.3B shows a plot that refers to RNA sequencing (RNA seq), histonechromatin immunoprecipitation sequencing (ChIP-seq) and Capture Cprofiles of PVT1/MYC gene. Capture C shows chromosomal interactionsbetween the c-Myc promoter and the super-enhancer. FIG. 3C shows a plotthat refers to RNA seq and histone ChIP-seq of EPAS1 gene. HistoneChIP-Seq validated gained super-enhancers at PVT1/MYC (FIG. 3B) andEPAS1 (FIG. 3C) loci overlapping with a renal cell carcinoma risk allelerespectively. FIG. 3D shows a heatmap of The Cancer Genome Atlas (TCGA)RNA-seq data indicating that genes associated with top 10 gainedenhancers are upregulated in tumours while genes associated with top 10lost enhancers are downregulated. This tumour-specificity is restrictedto clear cell renal cell carcinoma, but not the other two renalcellcarcinoma subtypes, papillary and chromophobe. Without being boundby theory, it is thought that ZNF395, SLC28A1, SMPLD3A, VEGFA and EGLN3are able to distinguish clear cell renal cell carcinoma from other majorrenal cell carcinoma subtypes, based on p-value and tumour/normal ratio(T/N) shown. FIG. 3E refers to a graph with expression of ZNF395 andSMPDL3A measured in a panel of normal kidney cell lines and clear cellrenal cell carcinoma cell lines by real time PCR (RT-qPCR). FIG. 3Fshows an immunoblot comparing protein expression of ZNF395 in a panel ofclear cell renal cell carcinoma cell lines. FIG. 3G refers to imagesthat indicate pooled siRNA against ZNF395 inhibits colony formation ofclear cell renal cell carcinoma cell lines A-498 and 786-O but not HK-2normal immortalized kidney cells. Pooled siRNA against SMPLD3A inhibitscolony formation of A-498 but not 786-O. FIG. 3H shows a graph of siRNAknockdown efficiency of SMPDL3A and ZNF395 as measured by real time PCR(RT-qPCR) in HK-2, 786-O and A498 cells. FIG. 3I refers to a plot ofhistone ChIP profile with H3K27ac ChIP-seq showing an active ZNF395super-enhancer only in clear cell renal cell carcinoma cells (A-498 and786-O) but not normal kidney cells (PCS-400, HK-2). FIG. 3J refers toplots of histone ChIP profile with H3K27ac and H3K4me3 ChIP-seq oftumour/normal pair showing that SMPLD3A or SLC28A1 is associated with aclear cell renal cell carcinoma specific super enhancer. FIG. 3K (FIGS.3Ki, 3Kii and 3Kiii) refers to a plot of histone ChIP-seq profile withH3K27ac, H3K4me3 and H3K4me1 ChIP-seq of tumour/normal pair showing thegain of promoters and enhancers in tumours for genes SLC6A3, EGLN3 orVEGFA. FIG. 3L to FIG. 3P refers to graphs showing expression dataobtained from The Cancer Genome Atlas (TCGA). FIG. 3L shows expressionof SMPDL3A in a panel of cancers, with the highest expression beingpresent in clear cell renal cell carcinoma (KIRC) (TCGA symbol for clearcell renal cell carcinoma) FIG. 3M shows expression of SLC28A1 in apanel of cancers, with the highest expression being present in clearcell renal cell carcinoma (KIRC). FIG. 3N shows expression of SLC6A3 ina panel of cancers, with the highest expression being present in clearcell renal cell carcinoma (KIRC). FIG. 3O shows expression of VEGFA in apanel of cancers, with the highest expression being present in clearcell renal cell carcinoma. FIG. 3P shows expression of EGLN3 in a panelof cancers, with the highest expression being present in clear cellrenal cell carcinoma (KIRC). FIG. 3Q refers to a box plot with TheCancer Genome Atlas (TCGA) RNA-seq data that shows exclusiveoverexpression of ZNF395 amongst 12 cancer types. FIG. 3R shows a graphreferring to shRNA knockdown efficiency of ZNF395 levels measured byreverse transcription polymerase chain reaction (RT-PCR) in 786-O andA-498 cells. FIG. 3S illustrates an immunoblot referring to shRNAknockdown efficiency of ZNF395 levels measured by immunoblotting in786-O and A-498 cells. FIG. 3T shows images of ZNF395 inhibition by twoshRNA clones that decrease colony formation in 786-O and A-498 cells.FIG. 3U refers to graphs of ZNF395 inhibition by two shRNA clones thatdecrease in vitro proliferation. FIG. 3V shows a graph of ZNF395inhibition by two shRNA clones that increases apoptosis measured bycleavage of Caspase3/7 substrate. *p-value <0.05, two-sided t-test. FIG.3W shows histograms of Annexin V staining analyzed by flow cytometryafter ZNF395 shRNA knockdown in 786-O and A-498 cells. FIG. 3X refers toline graphs showing ZNF395 inhibition by shRNA that leads to totalelimination of A-498 tumours in vivo and delayed tumour growth in 786-Ocells. Negative control (NC): n=7, shZNF395-1: n=7, shZNF395-2: n=6

FIG. 4 illustrates that VHL deficiency remodels clear cell renal cellcarcinoma enhancers. FIG. 4A show graphs referring to in vitroproliferation of 786-O, A-498 and 12364284 cell lines with and withoutVHL restoration. Proliferation rates were measured with CellTiterGlo,and normalized to day of seeding. EV refers to empty vector control andVHL refers to wild-type VHL restored. FIG. 4B refers to images of invitro colony formation of 786-O, A-498 and 12364284 cell lines with andwithout VHL restoration. Rates of colony formation were measured byseeding 10,000 cells in the well and allowing colonies to form until thewells are confluent. EV refers to empty vector control and VHL refers towild-type VHL restored. FIG. 4C shows graphs referring to apoptosismeasured by cleavage of caspase3/7 substrates and normalized to emptyvector controls of 786-O, A-498 and 12364284 cell lines, with andwithout VHL restoration. EV refers to empty vector control and VHLrefers to wild-type VHL restored. FIG. 4D illustrates a graph where invivo growth of 786-O subcutaneous tumours in nude mice is compared forisogenic cells with and without VHL restoration. EV refers to emptyvector control and VHL refers to wild-type VHL restored. FIG. 4E showsdot plots with log fold changes of H3K27ac chromatin immunoprecipitationsequencing (ChIP-seq) signals at gained promoters, gained enhancers andgained super-enhancers as defined in the primary clear cell renal cellcarcinoma dataset after VHL restoration in 786-O cells. Dots representcis-regulatory elements with significant changes (p-value <0.05,negative binomial) in H3K27ac levels after VHL restoration. The numberand percentage of altered regions (p-value <0.05, negative binomial) areshown at the upper and lower right corners. FIG. 4F, FIG. 4G and FIG. 4Hshows dot plots with log fold changes of H3K27ac ChIP-seq signals atgained promoters, gained enhancers and gained super-enhancers after VHLrestoration in (FIG. 4F) A-498 cells, (FIG. 4G) 12364284 cells and (FIG.4H) 40911432 cells. Dots represent p-value<0.05. The number andpercentage of altered regions are shown at the upper and lower rightcorners. EV refers to empty vector control and VHL refers to wild-typeVHL restored. FIG. 4I shows box plots with read coverage of H3K27acChIP-seq at VHL-responsive enhancers in VHL-mutant clear cell renal cellcarcinoma cell lines compared to VHL-wild-type clear cell renal cellcarcinoma, normal kidney cell lines and 31 other cancer cell lines.Enhancers with H3K27ac depletion or enrichment after VHL restoration areshown. FIG. 4J refers to a box plot that shows changes in expression ofgenes linked to VHL-responsive tumour enhancers after VHL restoration in786-O cells. *p-value <0.05, two-sided t-test. FIG. 4K shows a box plotwith changes of gene expression linked to VHL-responsive tumourenhancers in 12364284 cells. *p-value value <0.05, two-sided t-test.FIG. 4L refers to a bar graph with frequency of gained enhancers showingH3K27ac depletion after VHL restoration in patients. FIG. 4M shows aheatmap with unsupervised hierarchal clustering of differential H3K27acChIP-seq signals at gained enhancers showing H3K27ac depletion after VHLrestoration. FIG. 4N shows a plot with H3K27ac ChIP-seq signals of all10 tumour/normal pairs at the ZNF395 super-enhancer. FIG. 4O, FIG. 4Pand FIG. 4Q show plots of histone ChIP seq signals with examples of lostVHL-responsive enhancer/super-enhancers associated with EGFR (FIG. 4O),CCND1 (FIG. 4P) and ITGB3 (FIG. 4Q) in 786-O cells. FIG. 4R show plot ofhistone ChIP signals with examples of lost VHL-responsive enhancerassociated with SLC2A1 in 786-O cells. FIG. 4S show plot of histone ChIPseq signals with examples of lost VHL-responsiveenhancer/super-enhancers associated with VEGFA in 786-O cells. FIG. 4Tshow plot of histone ChIP signals with examples of lost VHL-responsiveenhancer associated with HK2 in 786-O cells. FIG. 4U shows dot plot ofPearson's correlation of log fold changes of H3K27ac and H3K4me1 in786-O and 12364284 after VHL restoration. (removed as there is no colourin figure) FIG. 4V shows dot plot of Pearson's correlation of log foldchanges of H3K27ac and H3K27me3 in 786-O and 12364284 after VHLrestoration. FIG. 4W refers to heatmap with log fold changes of H3K27ac,H3K4me1 and H3K27me3 signals at gained enhancers showing H3K27acdepletion after VHL restoration in 786-O cells.

FIG. 5 illustrates that HIF2α is enriched at enhancers of VHL-responsivetumour tumours. FIG. 5A refers to a table with motif analysis of gainedenhancers using HOMER, revealing significant enrichment of AP-1 family,ETS family, NFκB and HIF1α/2α (hypergeometric test). Lost enhancers wereused as background in the motif search to identify tumour-specifictranscription factors. FIG. 5B shows an immunoblot with proteinexpressions of putative transcription factors enriched at gainedenhancers in 9 tumour cell lines (4 commercial cell lines and 5patient-derived cell lines) and 2 normal cell lines. ACHN is a papillaryrenal cell carcinoma cell line. FIG. 5C shows scatter plots with geneexpression of selected transcription factors in 73 pairs of normalkidney and clear cell renal cell carcinoma tumours of the The CancerGenome Atlas (TCGA) cohort (RNA-Seq dataset). ***p-value <0.001,**p-value <0.01, n.s. (not significant), paired t-test. FIG. 5Dillustrates graphs showing that chromatin immunoprecipitation sequencing(ChIP-seq) validated the enrichment of transcription factors in gainedenhancers over lost enhancers. FIG. 5E refers to an immunoblot withprotein expression of transcription factors shown in 786-O and 12364284cells with and without wild-type VHL. FIG. 5F illustrates line graphs oftranscription factor binding at VHL-responsive gained enhancers thatshows enrichment of HIF2α and HIF1β at enhancers with H3K27ac depletionover regions with H3K27ac enrichment after VHL restoration. FIG. 5Grefers to pie charts with distribution of exogenous HIF1α and endogenousHIF2α ChIP-seq binding sites in 786-O cells annotated using ChIPseeker.FIG. 5H shows pie charts of ChIP-Seq data that shows distribution ofexogenous HIF1α and endogenous HIF2α binding at altered promoters andenhancers in 786-O cells that have been genetically engineered tooverexpress HIF1 α. FIG. 5I shows pie charts of distribution ofendogenous HIF1α and HIF2α ChIP-seq binding sites in 40911432 cellsannotated using ChIPseeker. FIG. 5J shows pie chart of ChIP-Seq thatshows distribution of endogenous HIF1α and HIF2α binding at alteredpromoters and enhancers in 40911432 cells. FIG. 5K refers to graph thatshows transcription factor binding at VHL-responsive enhancers showinghigher enrichment of HIF2α than HIF1α at enhancers with H3K27acdepletion after VHL restoration over regions with H3K27ac enrichmentafter VHL restoration. FIG. 5L refers to plot of ChIP Seq with exampleof a VHL-responsive enhancer near UBR4 with only HIF2α binding but notHIF1α binding. FIG. 5M refers to plot of ChIP Seq with example of aVHL-responsive super-enhancer near CM/P with only HIF2α binding but notHIF1α binding.

FIG. 6 illustrates that HIF2α-HIF1β bound enhancers modulate geneexpression. FIG. 6A refers to dot plots with Pearson's correlation ofgene expression changes after either VHL restoration or HIF2α siRNAknockdown at all genes or genes adjacent to HIF2α binding sites. FIG. 6Brefers to dot plots with Pearson's correlation of H3K27ac changes afterVHL restoration and HIF2α siRNA knockdown at either all gained enhancersor HIF2α-bound enhancers adjacent to binding sites. FIG. 6C refers todot plots with Pearson's correlation of H3K27ac changes after VHLrestoration and HIF2α siRNA knockdown at either all gainedsuper-enhancers or HIF2α-bound super-enhancers adjacent to bindingsites. FIG. 6D refers to plots of histone chromatin immunoprecipitationsequencing (ChIP-Seq) profiles showing changes in RNAseq and H3K27acChIP-Seq signals after VHL restoration or HIF2α siRNA knockdown atZNF395 super-enhancer (SE), together with binding profiles oftranscription factors enriched at enhancers. FIG. 6E refers to graphsshowing both VHL restoration and HIF2α siRNA knockdown decreasesexpression of genes with HIF2α-bound enhancers in 786-O cells. *p-value<0.05, two-sided t-test. FIG. 6F refers to graphs showing both VHLrestoration and HIF2α siRNA knockdown decrease enhancer activitiesmeasured by luciferase reporter assay in 786-O cells. *p-value <0.05,two-sided t-test. FIG. 6G refers to a column graph showing RT-qPCRmeasurement of ZNF395 expression in four wild-type clones and fourclones with ZNF395 enhancer depleted by CRISPR. Depleted region has thehighest HIF2α binding at ZNF395 super-enhancer in 786-O cells indicatedby the back bar above the scissors (deleted region indicated in FIG.6D). *p-value <0.05, two-sided t-test.

FIG. 7 shows that VHL restoration reduces p300 recruitment but preservespromoter-enhancer interactions. FIG. 7A shows a line graph of theenrichment of p300 binding at gained and lost enhancers based onchromatin immunoprecipitation sequencing (ChIP-Seq). FIG. 7B refers to acolumn graph showing the percentage of overlap between HIF2α and othertranscription factors. FIG. 7C refers to a heatmap of ChIP-Seq bindingprofiles of HIF2α and p300. FIG. 7D shows an immunoblot of the proteinexpression of p300 with and without VHL in 786-O and 12364284 cells asmeasured by immunoblotting. FIG. 7E shows a graph referring to ChIP-qPCRof p300 binding at enhancers with and without VHL restoration in 786-Ocells. NC refers to negative control regions. FIG. 7F refers to a graphshowing the ChIP-qPCR of p300 binding at enhancers with and withoutHIF2α siRNA knockdown in 786-O cells. NC refers to negative controlregions. FIG. 7G shows scatter plots referring to correlation ofenhancer interactions measured by Capture-C(RPM—reads per million)between 786-O cells with and without VHL restoration at bothVHL-responsive and non-VHL-responsive enhancers. FIG. 7H shows a plotreferring to Capture-C that shows that VEGFA enhancer-promoterinteractions are maintained even after VHL restoration. E refers toenhancer and P refers to promoter. FIG. 7I shows a diagram with theschematics of VHL-driven enhancer aberration in clear cell renal cellcarcinoma. FIG. 7J refers to a plot with histone ChIP Seq profile ofH3K27ac ChIP-seq and Capture C of 786-O (clear cell renal cell carcinomacell line) and KATO III (gastric cancer cell line) showing that theSLC2A1 enhancer is specific to clear cell renal cell carcinoma.

FIG. 8 (FIGS. 8A to 8C) shows graphs of analysis from exosomes obtainedfrom A498 (clear cell renal cell carcinoma cell line) and HK-2 (normalkidney cell line). Each graph shows the level of the respective marker(as denoted by the title of each graph) that was detected based onexosomes secreted from the respective cell lines based on the graphlegend. The y-axis of each graph shows gene expression of these markersas measured by quantitative polymerase chain reaction (qPCR).

FIG. 9 shows a heatmap with microarray data analysis from patientcohorts with clear cell renal cell carcinoma (ccRCC) or benignoncocytoma (B). VEGFA, EGLN3, ZNF395, SMPDL3A, SLC6A3 and SLC28A1expression levels were compared between benign oncocytoma and clear cellrenal carcinoma. A higher Z score indicates higher expression levels.

DETAILED DESCRIPTION OF THE PRESENT INVENTION

Renal cell carcinoma (RCC) is the most common type of kidney cancer inadults, with clear cell renal cell carcinoma (ccRCC) being one of thecommon subtypes of renal cell carcinoma. Other subtypes of renal cellcarcinoma include, for example, papillary renal cell carcinoma (pRCC)and chromophobe renal cell carcinoma (crRCC). One particular challengein the treatment of kidney tumours is the range of histologies andtumour phenotypes that a renal mass can represent. A kidney tumour rangefrom benign to clinically indolent malignancy to aggressive disease.Examples of aggressive disease include, but are not limited to, clearcell renal cell carcinoma (ccRCC). Kidney cancers of various subtypeshave diverse treatment response rates and variable prognoses. Therefore,the key to proper treatment is accurate diagnosis of the differentsubtypes of renal cell carcinomas.

Current methods of diagnosis include, but are not limited to, invasivemethods involving histologies from tumour biopsies, such as, staining ofglycogens by special stains, contrast-enhanced computed tomography (CT)scan (which demonstrates high vascularity of the tumours), ultrasoundimaging or magnetic resonance imaging (MRI). However, invasiveprocedures causes patient discomfort, require local or generalanaesthesia and can be, relatively expensive. Histologies from biopsiesand imaging methods including CT scan, MRI and ultrasound imaging, arealso unable to detect tumour stages accurately, resulting in frequentmisdiagnosis. Another option to identify clear cell renal cell carcinomapatients is through detection of biomarkers. However, there is currentlyno clinically validated biomarker for diagnosis of clear cell renal cellcarcinoma.

In view of the above problems, the inventors of the present disclosurehave provided biomarker(s) for identifying clear cell renal cellcarcinoma. Accordingly, in one example, there is disclosed one or moreclear cell renal cell carcinoma biomarkers.

As used herein, the term “clear cell renal cell carcinoma” or “ccRCC”refers to the most common subtype of a kidney cancer, namely renal cellcarcinoma (RCC). Kidney cancer refers to cancer that forms in tissues ofthe kidney, which is the organ that filters waste products from theblood. Kidney is also involved in regulating blood pressure, electrolytebalance and red blood cell production in the body. Each kidney isattached to a ureter, a tube that carries excreted urine to the bladder.Renal cell carcinoma is a kidney cancer that originates in the lining ofthe proximal convoluted tubule, a part of the very small tubes in thekidney that transport primary urine. Renal cell carcinoma is classifiedas an adenocarcinoma. The symptoms and implications accompanying renalcell carcinoma are well known in the art, for example hematuria (bloodin the urine), low back pain or pain in the flank and/or noticeable lumpin the flank. Clear cell renal cell carcinoma, which is the most commonsubtype of renal cell carcinoma, accounts for 75% to 85% of all renalcell carcinoma, and is also the most aggressive type of renal cellcarcinoma. Clear cell renal cell carcinoma is associated with geneticlesions in chromosome 3p, encompassing the von Hippel-Lindau gene. Ongross examination, clear cell renal cell carcinomas are typically goldenyellow and often develop hemorrhage and infarction with formation ofcysts within the tumour. Clear cell renal cell carcinoma is typicallycharacterized by malignant epithelial cells with clear cytoplasm and acompact alveolar or acinar growth pattern interspersed with intricate,arborizing vasculature.

As used herein, the term “tumour” refers to a group of abnormal cellsthat form lumps or growth. A tumour can be cancerous (malignant),non-cancerous (benign) or pre-cancerous. Benign tumour usually consistsof angiomyolipoma and oncocytoma. Angiomyolipoma is easy todifferentiate based on imaging, while being difficult to differentiateoncocytoma with imaging studies.

As used herein, the term “carcinoma” refers to a type of cancer thatstarts in cells that make up the skin (also known as epithelial cells)of the tissue lining organs, for example, but not limited to, the liveror kidneys. Common types of carcinoma include, but are not limited to,basal cell carcinoma, squamous cell carcinoma and renal cell carcinoma.In one example, clear cell renal cell carcinoma refers to malignanttumours, while oncocytoma is or represents benign tumours. In anotherexample, benign oncytomas are low in SLC28A1, VEGFA, ZNF395, EGLN3 andSLC6A3.

When confronted with a renal mass, it is difficult to differentiatebetween malignant or benign tumour. Benign tumours usually consist ofangiomyolipoma and oncocytoma. Differentiation of angiomyolipoma can beperformed with imaging studies, as performed in the art. However, it isdifficult to differentiate oncocytoma based on imaging studies alone.Thus, in one example, there is disclosed a method for determiningwhether a renal mass sample is benign or malignant. In another example,the method method of determining whether a renal mass sample is benignor malignant, the method comprising obtaining a sample from the renalmass of a subject;

-   -   determining the levels or the presence or absence of the        biomarker set as disclosed herein in the sample. In another        example, the increase in levels of the biomarker set in such a        renal mass sample, compared to a benign sample, indicates that        the sample is malignant. In yet another example, the method of        determining whether a renal mass sample is benign or malignant        comprises obtaining a sample from the renal mass of a subject;        determining the levels or the presence or absence of the        biomarker set as disclosed herein in the sample;        wherein the increase in levels of the biomarker set compared to        a benign sample indicates that the sample is malignant.

As used herein, the term “biomarker” refers to molecular indicators of aspecific biological property, a biochemical feature or facet that can beused to determine the presence or absence and/or severity of aparticular disease or condition. In the present disclosure, the term“biomarker” refers to a polypeptide or a nucleic acid sequence encodingthe polypeptide, a fragment or variant of a polypeptide being associatedwith clear cell renal cell carcinoma. In addition to a polypeptide or anucleic acid sequence encoding the polypeptide, a fragment or variant ofsuch a polypeptide being associated with clear cell renal cell carcinomapeptides as disclosed herein, the biomarker also refers to metabolitesor metabolized fragments of the expressed polypeptide. A person skilledin the art would understand that a metabolite of one of the biomarkersreferred to herein can still retain the capability of being used asbiomarker for the methods described herein. It is also noted that someof the biomarkers in the biomarker set can be present in their variantform or metabolized form while others are still intact. The term“variant” as used herein includes a reference to substantially similarsequences. Generally, nucleic acid sequence variants of the inventionencode a polypeptide which retains qualitative biological activity incommon with the polypeptide encoded by the “non-variant” nucleic acidsequence. Variants of said polypeptide include polypeptides that differin their amino acid sequence due to the presence of conservative aminoacid substitutions. For example, such variants have an amino acidsequence being at least 80%, at least 90%, at least 95%, at least 98%,or at least 99% identical over the entire sequence region to the aminoacid sequences of the “non-variant” polypeptides. Variants can beallelic variants, splice variants or any other species-specifichomologs, paralogs, or orthologs. In one example, the percentage ofidentity can be determined by known in the art algorithms. The sequenceidentity values recited above in percent (%) are to be determined,preferably, using programs known in the art, for example, BLASTp and thelike. Variants can be made using, for example, the methods of proteinengineering and site-directed mutagenesis as is well known in the art.

Conservative amino acid substitution tables providing functionallysimilar amino acids are well known to one of ordinary skill in the art.The following six groups are examples of amino acids that are consideredto be conservative substitutions for one another: i) Alanine (A), Serine(S), Threonine (T); ii) Aspartic acid (D), Glutamic acid (E); iii)Asparagine (N), Glutamine (Q); iv) Arginine (R), Lysine (K); v)Isoleucine (I), Leucine (L), Methionine (M), Valine (V); and vi)Phenylalanine (F), Tyrosine (Y), Tryptophan (W).

A non-conservative amino acid substitution can result from changes in:i) the structure of the amino acid backbone in the area of thesubstitution; ii) the charge or hydrophobicity of the amino acid; oriii) the bulk of an amino acid side chain. Substitutions generallyexpected to produce the greatest change in protein properties are thosein which i) a hydrophilic residue is substituted for (or by) ahydrophobic residue ii) a proline is substituted for (or by) any otherresidue; iii) a residue having a bulky side chain, for example,phenylalanine, is substituted for (or by) one not having a side chain,for example, glycine; or iv) a residue having an electropositive sidechain, for example, lysyl, arginyl, or histadyl, is substituted for (orby) an electronegative residue, for example, glutamyl or aspartyl.

As defined herein, the terms “peptide”, “protein”, “polypeptide”, and“amino acid sequence” are used interchangeably herein to refer topolymers of amino acid residues of any length. The polymer can be linearor branched, it can comprise modified amino acids or amino acidanalogues, and it can be interrupted by chemical moieties other thanamino acids. The terms also encompass an amino acid polymer that hasbeen modified naturally or by intervention; for example disulfide bondformation, glycosylation, lipidation, acetylation, phosphorylation, orany other manipulation or modification, such as conjugation with alabelling or bioactive component. The term peptide encompasses two ormore naturally occurring or synthetic amino acids linked by a covalentbond (for example, an amide bond). The amino acid residues are joinedtogether through amide bonds. When the amino acids are alpha-aminoacids, either the L-optical isomer or the D-optical isomer can be used,the L-isomers being preferred in nature. The term polypeptide or proteinas used herein encompasses any amino acid sequence and includes, but isnot be limited to, modified sequences such as glycoproteins. The termpolypeptide is specifically intended to cover naturally occurringproteins, as well as those that are recombinantly or syntheticallyproduced.

In one example, the clear cell renal cell carcinoma protein biomarkerset includes at least two selected from the group consisting of ZNF395,SMPDL3A, SLC28A1, SLC6A3, VEGFA, EGLN3, and variants thereof, whereinone of the at least two biomarkers is SMPDL3A or SLC28A1. In anotherexample, the clear cell renal cell carcinoma (ccRCC) biomarker setcomprises at least two biomarkers selected from the group consisting ofZNF395, SMPDL3A, SLC28A1, SLC6A3, VEGFA, and EGLN3. In another example,one of the at least two biomarkers is SMPDL3A or SLC28A1. In yet anotherexample, the biomarkers are proteins, or nucleic acids encoding thesame, or variants thereof.

Also disclosed herein is a composition comprising the biomarker set asdisclosed herein.

As used herein, the term “ZNF395”, also known as HDBP-2, HDRF-2, PBF orPRF-1, refers to both a gene and the expressed polypeptide thereof, bothof which are associated with Huntington Disease. This gene is ahypoxia-inducible transcription factor that is controlled by I_(K)Bsignalling and activates genes involved in innate immune response andcancer. It has been found to be overexpressed in various human cancers,particularly in response to hypoxia. ZNF395 has also been shown to playa role in papillomavirus gene transcription.

As used herein “SMPDL3A”, also known as sphingomyelin phosphodiesteraseacid like 3A, or ASML3a, refers to a gene and the expressed polypeptidethereof, both of which has in vitro nucleotide phosphodiesteraseactivity with nucleoside triphosphates, such as for example, ATP. Thisprotein has no activity with nucleoside diphosphates, and no activitywith nucleoside monophosphates. SMPDL3A has in vitro activity withCDP-choline and CDP-ethanolamine, with no spingomyelin phosphodiesteraseactivity. As mentioned in the experimental section below, SMPDL3A is atarget of a master regulator of cholesterol metabolism.

As used herein, the term “SLC28A1”, also known as concentrativenucleoside transporter 1 (CNT1), HCNT1 or solute carrier family 28member 1, refers to a gene and the expressed polypeptide thereof, bothof which is sodium dependent and pyrimidine selective. SLC28A1 exhibitstransport characteristics of the nucleoside transport system cit or N2subtype (N2/cit). SLC28A1 also transports the antiviral pyrimidinenucleoside 3′-azido-3′-deoxythymidine (AZT) and 2′,3′-dideoxycytidine(ddC). SLC28A1 is involved in the uptake of nucleoside-derived drugsusing antiviral and chemical therapies.

As used herein, the term “SLC6A3”, also known as solute carrier family 6member 3, DAT, dopamine transporter, sodium dependent dopaminetransporter, or PKDYS, refers to a gene or the expressed polypeptidethereof, both of which encodes a dopamine transporter, which is a memberof the sodium and chloride dependent neurotransmitter transporterfamily. SLC6A3 terminates the action of dopamine by its high affinitysodium-dependent re-uptake into presynaptic terminals. Variation of thenumber of repeats of this gene or the expressed polypeptide thereof isassociated with idiopathic epilepsy, attention-deficit hyperactivitydisorder, dependence on alcohol and cocaine, susceptibility to Parkinsondisease and protection against nicotine dependence.

As used herein, the term “VEGFA”, also known as vascular endothelialgrowth factor A, vascular permeability factor, VEGF, VPF or MVCD1,refers to a gene or the expressed polypeptide thereof that is a memberof the PDGF/VEGF growth factor family. VEGFA encodes a heparin-bindingprotein. It is a growth factor that induces proliferation and migrationof vascular endothelial cells and is essential for both physiologicaland pathological angiogenesis. Disruption of this gene in mice resultedin abnormal embryonic blood vessel formation. This gene is up-regulatedin many known tumours and its expression is correlated with tumour stageand progression. Variants of this gene has been reported, including, butnot limited to, allelic variants associated with microvascularcomplications of diabetes 1 (MVCD1) and atherosclerosis, alternativelyspliced transcript variants encoding different isoforms, alternativetranslation initiation from upstream non-AUG (CUG) codons (resulting inadditional isoforms), and C-terminally extended isoforms produced by useof an alternative in-frame translation termination codon via a stopcodon read-through mechanism (with this isoform being antiangiogenic).

As used herein, the term “EGLN3”, also known as Egl-9 family hypoxiainducible factor 3, prolyl hydroxylase domain-containing protein 3,hypoxia-inducible factor prolyl hydrolase 3, HIF-prolyl hydroxylase 3,HIF-PH3, HPH-1, HPH-3, PHD3, HIFP4H3, Egl Nine-like protein 3 isoform,refers to a gene or the expressed polypeptide thereof associated withdiseases including hypoxia and chronic mountain sickness. Relatedpathways of this protein include HIF-1 signaling pathway and HIFrepressor pathways. EGLN3 functions as a cellular oxygen sensor thatcatalyzes the post-translational formation of 4-hydroxyproline inhypoxia-inducible factor (HIF) alpha proteins under normoxic conditions.

The clear cell renal cell carcinoma (ccRCC) biomarker set disclosedherein can be used in combination with two or more further biomarkers,wherein one of the at least two biomarkers is SMPDL3A or SLC28A1. Thus,in one example, the clear cell renal cell carcinoma protein biomarkerset comprises any two, three, four, five or all six biomarkers. Inanother example, the biomarker set as disclosed herein comprises atleast three biomarkers. In another example, the biomarker set asdisclosed herein comprises at least four biomarkers. In another example,the biomarker set as disclosed herein comprises at least fivebiomarkers. In another example, the biomarker set as disclosed hereincomprises at least six biomarkers.

In another example, the biomarker set or the biomarkers are, but are notlimited to, ZNF395, SMPDL3A, SLC28A1, SLC6A3, VEGFA and EGLN3, andcombinations thereof. In one example, the clear cell renal cellcarcinoma biomarker set or biomarkers comprise or consist of SMPDL3A andSLC28A1. In another example, the clear cell renal cell carcinomabiomarker set or biomarkers comprise or consist of SMPDL3A and ZNF395.In yet another example, the clear cell renal cell carcinoma biomarkerset or biomarkers comprise or consist of SMPDL3A and SLC6A3. In stillanother example, the clear cell renal cell carcinoma biomarker set orbiomarkers comprise or consist of SMPDL3A and VEGFA. In yet anotherexample, the clear cell renal cell carcinoma biomarker set or biomarkerscomprise or consist of SMPDL3A and EGLN3. In one example, the clear cellrenal cell carcinoma biomarker set or biomarkers comprise or consist ofSLC28A1 and ZNF395. In yet another example, the clear cell renal cellcarcinoma biomarker set or biomarkers comprise or consist of SLC28A1 andSLC6A3. In still another example, the clear cell renal cell carcinomabiomarker set or biomarkers comprise or consist of SLC28A1 and VEGFA. Inyet another example, the clear cell renal cell carcinoma biomarker setor biomarkers comprise or consist of SLC28A1 and EGLN3. In one example,the clear cell renal cell carcinoma biomarker set or biomarkers compriseor consist of SMPL3A, SLC28A1 and ZNF395. In yet another example, theclear cell renal cell carcinoma biomarker set or biomarkers comprise orconsist of SMPL3A, SLC28A1 and SLC6A3. In still another example, theclear cell renal cell carcinoma biomarker set or biomarkers comprise orconsist of SMPL3A, SLC28A1 and VEGFA. In yet another example, the clearcell renal cell carcinoma biomarker set or biomarkers comprise orconsist of SMPL3A, SLC28A1 and EGLN3. In one example, the clear cellrenal cell carcinoma biomarker set or biomarkers comprise or consist ofSMPDL3A, ZNF395 and SLC6A3. In another example, the clear cell renalcell carcinoma biomarker set or biomarkers comprise or consist ofSMPDL3A, ZNF395 and VEGFA. In yet another example, the clear cell renalcell carcinoma biomarker set or biomarkers comprise or consist ofSMPDL3A, ZNF395 and EGLN3. In still another example, the clear cellrenal cell carcinoma biomarker set or biomarkers comprise or consist ofSMPDL3A, SLC6A3 and VEGFA. In yet another example, the clear cell renalcell carcinoma biomarker set or biomarkers comprise or consist ofSMPDL3A, SLC6A3 and EGLN3. In another example, the clear cell renal cellcarcinoma biomarker set or biomarkers comprise or consist of SMPDL3A,VEGFA and EGLN3. In still another example, the clear cell renal cellcarcinoma biomarker set or biomarkers comprise or consist of or consistof SLC28A1, ZNF395 and SLC6A3. In another example, the clear cell renalcell carcinoma biomarker set or biomarkers comprise or consist ofSLC28A1, ZNF395 and VEGFA. In another example, the clear cell renal cellcarcinoma biomarker set or biomarkers comprise or consist of SLC28A1,ZNF395 and EGLN3. In one example, the clear cell renal cell carcinomabiomarker set or biomarkers comprise or consist of SLC28A1, SLC6A3 andVEGFA. In another example, the clear cell renal cell carcinoma biomarkerset or biomarkers comprise or consist of SLC28A1, SLC6A3 and EGLN3. Inyet another example, the clear cell renal cell carcinoma biomarker setor biomarkers comprise or consist of SLC28A1, VEGFA and EGLN3. In oneexample, the clear cell renal cell carcinoma biomarker set or biomarkerscomprise or consist of SMPDL3A, SLC28A1, ZNF395 and SLC6A3. In anotherexample, the clear cell renal cell carcinoma biomarker set or biomarkerscomprise or consist of SMPDL3A, SLC28A1, ZNF395 and VEGFA. In yetanother example, the clear cell renal cell carcinoma biomarker set orbiomarkers comprise or consist of SMPDL3A, SLC28A1, ZNF395 and EGLN3. Instill another example, the clear cell renal cell carcinoma biomarker setor biomarkers comprise or consist of SMPDL3A, ZNF395, VEGFA and EGLN3.In yet another example, the clear cell renal cell carcinoma biomarkerset or biomarkers comprise or consist of SMPDL3A, ZNF395, SLC6A3 andVEGFA. In another example, the clear cell renal cell carcinoma biomarkerset or biomarkers comprise or consist of SMPDL3A, ZNF395, SLC6A3 andEGLN3. In yet another example, the clear cell renal cell carcinomabiomarker set or biomarkers comprise or consist of SMPDL3A, SLC6A3,VEGFA and EGLN3. In one example, the clear cell renal cell carcinomabiomarker set or biomarkers comprise or consist of SLC28A1, ZNF395,SLC6A3 and VEGFA. In yet another example, the clear cell renal cellcarcinoma biomarker set or biomarkers comprise or consist of SLC28A1,ZNF395, SLC6A3 and EGLN3. In still another example, the clear cell renalcell carcinoma biomarker set or biomarkers comprise or consist ofSLC28A1, ZNF395, VEGFA and EGLN3. In one example, the clear cell renalcell carcinoma biomarker set or biomarkers comprise or consist ofSMPDL3A, SLC28A1, ZNF395, SLC6A3 and VEGFA. In another example, theclear cell renal cell carcinoma biomarker set or biomarkers comprise orconsist of SMPDL3A, SLC28A1, ZNF395, SLC6A3 and EGLN3. In yet anotherexample, the clear cell renal cell carcinoma biomarker set or biomarkerscomprise or consist of SMPDL3A, SLC28A1, ZNF395, VEGFA and EGLN3. Instill another example, the clear cell renal cell carcinoma biomarker setor biomarkers comprise or consist of SMPDL3A, ZNF395, SLC6A3, VEGFA andEGLN3. In a further example, the clear cell renal cell carcinomabiomarker set biomarkers comprise or consist of SLC28A1, SLC6A3, VEGFAand EGLN3. In yet another example, the clear cell renal cell carcinomabiomarker set or biomarkers comprise or consist of SLC28A1, ZNF395,SLC6A3, VEGFA and EGLN3. In one example, the clear cell renal cellcarcinoma biomarker set or biomarkers comprise or consist of ZNF395,SMPDL3A, SLC28A1, SLC6A3, VEGFA and EGLN3.

The biomarkers of the present invention can be combined with oneanother, for example, as a biomarker set, thereby providing sensitiveand specific determination of clear cell renal cell carcinoma subjectsthought to suffer from clear cell renal cell carcinoma. The option ofcombining the biomarkers of the present disclosure provides astatistically reliable detection of clear cell renal cell carcinomas. Inone example, the presence of the two or more biomarkers in a sample isindicative of the presence of clear cell renal cell carcinoma. Inanother example, the presence of the biomarker set as disclosed hereinis indicative of the presence of clear cell renal cell carcinoma. Inanother example, the upregulation of the biomarker set in a sample isindicative of the presence of clear cell renal cell carcinoma. This canbe seen from the data provided in FIG. 3D, where statistical relevancebased on a p-value is provided for a list of markers.

As used herein, the term “upregulation” refers to an increased level ofexpression of a nucleic acid or a protein in a sample obtained from adisease subject, whereby the increase is compared to expression of thesame nucleic acid or protein in a control sample. In one example, thesubject is suffering from clear cell renal cell carcinoma. As disclosedherein, this upregulation can be depicted as, for example, but notlimited to, high tumour-normal ratios, low p-values or high levels ofmRNA expression. In one example, the expression levels of nucleic acidscan be measured, for example, by polymerase chain reaction (PCR). In oneexample, the polymerase chain reaction (PCR) is reverse transcriptionpolymerase chain reaction (RT-PCR), or real-time polymerase chainreaction (qPCR) or combinations thereof. It is noted that RT-PCR is usedto qualitatively detect gene expression through the creation ofcomplementary DNA (cDNA) transcripts from RNA, while qPCR is used toquantitatively measure the amplification of DNA using fluorescent dyes.qPCR is also referred to in the art as quantitative PCR, quantitativereal-time PCR, and real-time quantitative PCR.

As illustrated in the experimental section, the biomarkers of thepresent disclosure in particular ZNF395, SMPL3A and SLC28A1, have beenshown to be specific to clear cell renal cell carcinoma, and were shownto not be overexpressed in papillary and chromophobe renal cellcarcinomas, two other distinct renal cell carcinoma subtypes (FIG. 3D).ZNF395 exhibited tumour-normal ratio of about 7 in clear cell renal cellcarcinoma with p-value of 1×10⁻²², while showing little overexpressionin papillary and chromophobe renal cell carcinomas with tumour-normalratio of 1.2 (p=0.02) and 1.3 (p=0.06) respectively.

Furthermore, the experimental section, and for example, FIG. 3 , alsoshow that among the 12 types of cancer profiled by The Cancer GenomeAtlas (TCGA), ZNF395, SMPL3A, SLC28A1, SLC6A3, VEGFA and EGFA wereexclusively overexpressed in clear cell renal cell carcinoma tumours(KIRC). ZNF395 depletion in vivo further validates that ZNF395 plays animportant role in clear cell renal cell carcinoma tumourigenesis. ZNF395depletion significantly slowed in vivo tumour growth of 786-O clear cellrenal cell carcinoma cells. In addition, SMPDL3A and SLC28A1 are shownto be associated with clear cell renal cell carcinoma-specificsuper-enhancer.

As described in the experimental section of the present disclosure,analysis of exosomes in culture medium of cell cultures can beperformed, for example, by measuring levels of gene expression. Thisdata can be found, for example, in FIG. 8 . In one example, this can bedone by qPCR, which was performed on clear cell renal cell carcinomacell line (A498) and normal kidney cell lines (HK2). Results fromexosome analysis in the present disclosure shows higher expression ofZNF395, SMPL3A, VEGFA and EGLN3 in clear cell renal cell carcinoma celllines compared to normal kidney cell lines.

As used herein, the term “exosome” refers to a type of smallextracellular vesicle (EV), ranging from 30 to 200 nm in diameter. Theseexosomes can be isolated from cell culture media, as well as an array ofeukaryotic fluids. These fluids include, but are not limited to, blood,urine and sputum samples. Therefore, exosomes can be used to identifybiomarkers from liquid samples using non-invasive methods. Exosomes areeither released from the cell when multi-vesicular bodies fuse with theplasma membrane, or are released directly from the plasma membrane.These vesicles carry nucleic acid (for example, RNA and DNA) andproteins from, for example, the tumour in tumour-bearing subjects.Exosomes have been implicated in driving malignant cell behaviourincluding, but not limited to stimulation of tumour cell growth andsuppression of a host immune response. Therefore, exosomes are a viablesource for identifying biomarkers for cancer. Isolating exosomes fromspecific tissues also allows identification of tissue-specific ordisease-specific biomarkers. Briefly, in on example, exosome analysiscan be performed by ultracentrifugation from cells. After trypticdigestion, proteomic analysis can be performed, and candidate biomarkersare validated by, for example, methods known in the art, including butnot limited to, western blotting and immunohistochemistry. In oneexample, the exosomes are detected using the detection system and/or themethods disclosed herein. In another example, the exosomes are detectedand/or analysed using quantitative polymerase chain reaction (qPCR).

The terms “isolated” or “isolating” as used herein relates to abiological component (such as a nucleic acid molecule, protein ororganelle) that has been substantially separated or purified away fromother biological components in the cell of the organism in which thecomponent naturally occurs, i.e., other chromosomal andextra-chromosomal DNA and RNA, proteins and organelles. Nucleic acidsthat have been “isolated” include nucleic acids purified by standardpurification methods.

As illustrated in the experimental section of the present disclosure,the inventors of the present disclosure found that the biomarkers of thepresent disclosure can be detected in various sample types as describedherein. The term “sample”, as used herein, refers to single cells,multiple cells, fragments of cells, tissue, or body fluid, which hasbeen obtained from, removed from, or isolated from a subject. An exampleof a sample includes, but is not limited to, blood, stool, serum,saliva, urine, sputum, cerebrospinal fluid, bone marrow fluid, frozenfresh tissue of a tumour sample, or frozen fresh tissue of anon-diseased tissue harvested from sites distant from the tumour. Forexample, the biomarkers were clearly detected in solid samples, whichinclude, but are not limited to, solid tumour biopsy from suitableorgans, such as the kidney. Fresh-frozen normal-tumour tissues wereobtained from nephrectomy cases and normal tissues were harvested fromsites distant from the tumour. Normal-tumour tissues as described hereinor normal-tumour pair as described in the experimental section in otherwords means a tumour sample and a non-diseased sample that is obtainedfrom the same subject. The sample can include, but is not limited to,tissue obtained from the lung, the muscle, brain, liver, skin, pancreas,stomach, bladder, and other organs. In another example, the sampleincludes, but is not limited to, fluid samples derived from orcomprising bodily fluids, such as whole blood, serum, plasma, tears,saliva, nasal fluid, sputum, gastrointestinal fluid, exudate,transudate, fluid harvested from a site of an immune response, fluidharvested from a pooled collection site, bronchial lavage, a nucleatedcell sample, a fluid associated with a mucosal surface, hair, or skin,and urine. In one example, the fluid sample is liquid tumour biopsy,urine sample, blood sample, sputum sample or cell culture medium. Inanother example, the fluid sample contains exosomes suspected tocomprise the biomarkers or biomarker set as disclosed herein. In oneexample, the detection of the biomarkers in urine sample, blood sampleor sputum sample is desirable as it allows for non-invasive detection ofclear cell renal cell carcinoma in subjects.

In another example, there is provided a detection system for detectingthe biomarker as disclosed herein. In one example, the detection systemof the present disclosure comprises a receiving section to receive asample from a patient suspected to suffer from clear cell renal cellcarcinoma. In another example, the sample is suspected to comprise thetwo or more biomarkers of the present disclosure. In yet anotherexample, the detection system comprises a substance or substancescapable of detecting the two or more biomarkers of the presentdisclosure. In a further example, one of the at least two biomarkers isSMPDL3A or SLC28A1. In one example, the detection system of the presentdisclosure comprises a) a receiving section to receive a sample from apatient suspected to suffer from clear cell renal cell carcinoma, andwherein the sample is suspected to comprise the two or more biomarkersof the present disclosure, and b) a detection section comprising asubstance or substances capable of detecting the two or more biomarkers,or the biomarker set, of the present disclosure, wherein one of the atleast two biomarkers is SMPDL3A or SLC28A1.

In one example, the detection system comprises a receiving section toreceive a sample from a patient suspected to suffer from clear cellrenal cell carcinoma, and wherein the sample is suspected to comprisetwo, three, four, five or all six biomarkers, or a biomarker set, of thepresent disclosure. In one example, the receiving section can be abiochip, test strip, a real time polymerase chain reaction (qPCR)apparatus or microtiter plate. In one example, the sample can be fluidsamples, as described herein.

In one example, the detection system or method of the present disclosurecan require a fluid sample volume, such as, but not limited to, a samplevolume of between about 1 μl to about 30 ml, 1 μl to 5 μl, 4 μl to 10μl, 9 μl to 15 μl, 14 μl to 20 μl, 19 μl to 25 μl, 24 μl to 30 μl, 29 μlto 35 μl, 34 μl to 40 μl, 39 μl to 45 μl, 44 μl to 50 μl, 49 μl to 60μl, 59 μl to 80 μl, 79 μl to 100 μl, 99 μl to 150 μl, 149 μl to 200 μl,199 μl to 250 μl, 249 μl to 300 μl, 299 μl to 500 μl, 499 μl to 1 ml,999 μl to 5 ml, 4.99 ml to 10 ml, 9.99 ml to 20 ml and 19.99 ml to 30ml. In one example, the fluid or sample volume can be about 1 μl, about5 μl, about 10 μl, about 15 μl, about 20 μl, about 25 μl, about 30 μl,about 35 μl, about 40 μl, about 45 μl, about 50 μl, about 100 μl, about150 μl, about 200 μl, about 250 μl, about 300 μl, about 350 μl, about400 μl, about 450 μl, about 500 μl, about 550 μl, about 600 μl, about650 μl, about 700 μl, about 750 μl, about 800 μl, about 850 μl, about900 μl, about 950 μl, about 1 ml, about 2 ml, about 3 ml, about 4 ml,about 5 ml, about 6 ml, about 7 ml, about 8 ml, about 9 ml, about 10 ml,about 11 ml, about 12 ml, about 13 ml, about 14 ml, about 15 ml, about16 ml, about 17 ml, about 18 ml, about 19 ml, about 20 ml, about 21 ml,about 22 ml, about 23 ml, about 24 ml, about 25 ml, about 26 ml, about27 ml, about 28 ml, about 29 ml, to about 30 ml, or any values therebetween.

To assist in detecting the biomarkers of the present disclosure, thedetection system of the present disclosure can comprise a substancecapable of binding or specifically binding to two, three, four, five orall six biomarkers of the present disclosure. In one example, thesubstance is a biospecific capture reagent, such as, but not limited to,antibodies (or antigen-binding fragments thereof), interacting fusionproteins, aptamers or affibodies (which are non-immunoglobulin-derivedaffinity proteins based on a three-helical bundle protein domain), allof which can be chosen for their ability to recognize the biomarkerand/or variants thereof. Antibodies can include, but are not limited toprimary antibodies, secondary antibodies or horseradish peroxidase(HRP)-tagged secondary antibodies and the like. In one example, thesubstance includes antibodies known in the art to specifically recogniseZNF395, SMPDL3A, SLC28A1, SLC6A3, VEGFA or EGLN3.

In one example, the substance can be bound to a solid phase, wherein thebiomarkers can then be detected by mass spectrometry, or by eluting thebiomarkers from the biospecific capture reagents and detecting theeluted biomarkers by traditional matrix-assisted laserdesorption/ionisation (MALDI) or by surface-enhanced laserdesorption/ionization (SELDI). In another example, the detection systemcan be a biochip, test strip, qPCR apparatus, or microtiter plate.

In another example, the detection system comprising a receiving sectionand a detection section can be configured to detect one, two, three,four, five or all six biomarkers, or the biomarker set, as describedherein, individually, or in combination with one another. The detectionsystem, as disclosed herein, can also be configured to detect the one ormore biomarkers simultaneously or in any given sequence (in other words,one at time).

In another example, there is disclosed a method of determining whether asubject has or shows recurrence of clear cell renal cell carcinoma(ccRCC). In one example, the method comprises obtaining a sample from asubject. In another example, the method comprises detecting the presenceof the biomarker set of the present invention using a detection systemof the present invention, wherein the presence of the biomarker setdetermines that a subject has or shows recurrence of clear cell renalcell carcinoma. In yet another example, the method comprises a)obtaining a sample from a subject; and b) detecting the presence of thebiomarker set of the present invention using a detection system of thepresent invention, wherein the presence of the biomarker set determinesthat a subject has or shows recurrence of clear cell renal cellcarcinoma.

In yet another example, the method comprises detecting the presence ofthe biomarker set of the present invention obtained from a sample from asubject, using a detection system of the present invention, wherein thepresence of the biomarker set determines that a subject has or showsrecurrence of clear cell renal cell carcinoma.

As used herein, the term “patient” or “subject” or “individual”, whichcan be used interchangeably, relates to animals, for example mammals,including but not limited to, cows, horses, non-human primates, dogs,cats and humans. The subject or the patient of the present disclosurecan be suspected of suffering from, or have previously suffered from,clear cell renal cell carcinoma. In one example, the method of thepresent invention can be applied to a subject suspected of sufferingfrom clear cell renal cell carcinoma. In another example, the method ofthe present disclosure can be applied to a subject suspected of having arecurrence of clear cell renal cell carcinoma. The term “recurrence” asused herein refers to the return of or re-detection of clear cell renalcell carcinoma in a patient who has been deemed to be free of renalcarcinomas or, specifically, free of clear cell renal carcinoma.

The biomarkers, or the biomarker set, disclosed herein can be detectedin samples using methods known in the art. It is appreciated that theperson skilled in the art would understand which assays known in the artwould be suitable in detecting the biomarkers of the present disclosure.For example, detection of the biomarkers of the present disclosurerelates to the observance of presence or absence of the biomarkers.

Detection can be done directly or indirectly. Direct detection relatesto detection of the polypeptide based on a signal which is obtained fromthe polypeptide itself and the intensity of which directly correlateswith the number of molecules of the polypeptide present in the sample.Such a signal—sometimes referred to as intensity signal, can beobtained, for example, by measuring an intensity value of a specificphysical or chemical property of the polypeptide. Indirect measuringincludes measuring of a signal obtained from a secondary component (i.e.a component not being the polypeptide itself) or a biological read outsystem, for example, measurable cellular responses, ligands, labels, orenzymatic reaction products. The concept outlined above can also beapplied to genes, whereby the determination of the level of the gene canbe determined by measuring gene expression, either global or targetedgene expression, using methods known in the art. For example, thedetection can be carried out using molecular biological methods.

The molecular biological methods can include, but are not limited to,polymerase chain reaction (PCR), such as reverse transcriptionpolymerase chain reaction (RT-PCR), or real-time polymerase chainreaction (qPCR, also known as quantitative PCR); Western Blot, Dot Blot;mass spectrometry; nucleic acid sequencing; immunological methods, suchas enzyme-linked immunosorbent assay (ELISA) using antibodies; and thelike. For example, in the experimental section of the presentdisclosure, Western Blot, real-time quantitative PCR (qPCR) and nucleicacid sequencing are used.

In one example, the detection system detects exosomes using quantitativepolymerase chain reaction.

In one example, the indication as to whether the two or more biomarkers,or the biomarker set as disclosed herein, are present in a sampleobtained from the patient or whether the subject has or shows recurrenceof clear cell renal cell carcinoma can be made based on comparison ofthe two or more biomarkers, or the biomarker set as disclosed herein,with the same biomarkers in a control group. As use herein, a controlgroup includes disease-free subjects and/or samples from non-diseasedareas of the same or different subjects suffering from clear cell renalcell carcinoma. Control samples from the same or different subjects canalso be known as matched or unmatched pairs, respectively. The controlgroup can also be a non-cancerous sample obtained from a differentsubject with clear cell renal cell carcinoma; a subject that has adifferent renal cell carcinoma subtype; a subject with another type ofcancer; or a sample obtained from non-cancerous kidney cell lines. Anon-cancerous kidney cell line is, but is not limited to, HK-2 andPCS-400 cell lines. In one example, the clear cell renal cell carcinoma(ccRCC) sample and control sample are obtained from the same subject(normal-tumour pair or tumour-normal pair, as described herein).Therefore, the method also includes differentiation of clear cell renalcell carcinoma from other types of renal cell carcinoma or from anothertype of cancer.

In one example, there is disclosed a kit comprising a detection systemas described herein, and substances needed to carry out the method asdescribed herein. In one example, the kit comprises a detection buffer,a lysis buffer, and substance or substances as described herein.

In one example, the biomarkers, methods, detection system or kit of thepresent disclosure are used to identify clear cell renal cell carcinomain patients. The biomarkers, methods, detection system or kit of thepresent disclosure can be used for detecting or predicting recurrence inclear cell renal cell carcinoma patients who may or may not beundergoing treatment or had received treatment for clear cell renal cellcarcinoma.

In another example, there is disclosed a method of treating clear cellrenal cell carcinoma in a subject, wherein the method comprisesdetecting the biomarker set as described herein, and treating thesubject determined to suffer from clear cell renal cell carcinoma withan anti-clear cell renal cell carcinoma compound and/or treatment.

It will be appreciated that the biomarker set as disclosed herein can beused to detect whether a treatment being performed or which had beenperformed on a subject was successful or not. This is because there is adifference in biomarker expression level and/or presence or absence ofthe biomarker in diseased tissue when compared to non-diseased tissue.Thus, in one example, there is a method of detecting response of asubject to systemic treatment, the method comprising obtaining a samplefrom the subject; and determining the levels of the biomarker set asdefined herein, wherein a decrease in levels or an absence of thebiomarker set indicates that the subject is responsive to treatment.

Also disclosed herein is a method for detecting susceptibility of asubject to an anti-clear cell renal cell carcinoma treatment. Thismethod comprises determining the response of a sample from a diseasessubject when subjected to one or more anti-clear cell renal cellcarcinoma treatments based on the expression and/or presence or absenceof the biomarker set as disclosed herein. In one example, the anti-clearcell renal cell carcinoma treatment comprises anti-cancer treatment,antibodies and the like.

The data shown herein examines somatically altered super-enhancers,which enabled the identification of a master regulator thought to play akey role in the pathogenesis of clear cell renal cell carcinoma, ZNF395.This disclosure describes specific von Hippel-Lindau-dependent enhancerrequired for ZNF395 expression and shows the role of ZNF395 in clearcell renal cell carcinoma tumourigenesis in vitro and in vivo.

Epigenetic maps of this study reveal targets that contribute to clearcell renal cell carcinoma tumourigenesis. Extensive enhancer gains werefound around well-characterized hypoxia-related targets (VEGFA, CXCR4,HK2), SLC-mediated membrane transporters (SLC2A1, SLC2A2, SLC38A1),SLC16A family, and adipogenesis (PLIN2). Targets revealed in this studyinclude SMPDL3A, SLC28A1, SLC6A3, VECFA and EGLN3. SMPDL3A is a clearcell renal cell carcinoma-specific oncogene with a role in lipid andcholesterol metabolism. One finding from this epigenomic study is thetumourigenic requirement of ZNF395 in clear cell renal cell carcinoma.ZNF395 is also known as HDBP2 or papillomavirus binding factor (PBF).ZNF395 is required for the differentiation of mesenchymal stem cells toadipocytes, by partnering with PPARγ2 to promote adipogenesis. ZNF395has been shown to bind to the promoters of Huntington gene andinterferon-induced genes, and to cause upregulation of cancer-relatedgenes (MACC1, PEG10, CALCOCO1, and MEF2C) and proangiogenic chemokinesincluding IL6 and IL8 under hypoxia.

The invention illustratively described herein can suitably be practicedin the absence of any element or elements, limitation or limitations,not specifically disclosed herein. Thus, for example, the terms“comprising”, “including”, “containing”, etc. shall be read expansivelyand without limitation. Additionally, the terms and expressions employedherein have been used as terms of description and not of limitation, andthere is no intention in the use of such terms and expressions ofexcluding any equivalents of the features shown and described orportions thereof, but it is recognized that various modifications arepossible within the scope of the invention claimed. Thus, it should beunderstood that although the present invention has been specificallydisclosed by preferred embodiments and optional features, modificationand variation of the inventions embodied therein herein disclosed can beresorted to by those skilled in the art, and that such modifications andvariations are considered to be within the scope of this invention.

As used in this application, the singular form “a,” “an,” and “the”include plural references unless the context clearly dictates otherwise.For example, the term “a genetic marker” includes a plurality of geneticmarkers, including mixtures and combinations thereof.

As used herein, the term “about”, in the context of concentrations ofcomponents of the formulations, typically means +/−5% of the statedvalue, more typically +/−4% of the stated value, more typically +/−3% ofthe stated value, more typically, +/−2% of the stated value, even moretypically +/−1% of the stated value, and even more typically +/−0.5% ofthe stated value.

Throughout this disclosure, certain embodiments can be disclosed in arange format. It should be understood that the description in rangeformat is merely for convenience and brevity and should not be construedas an inflexible limitation on the scope of the disclosed ranges.Accordingly, the description of a range should be considered to havespecifically disclosed all the possible sub-ranges as well as individualnumerical values within that range. For example, description of a rangesuch as from 1 to 6 should be considered to have specifically disclosedsub-ranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4,from 2 to 6, from 3 to 6 etc., as well as individual numbers within thatrange, for example, 1, 2, 3, 4, 5, and 6. This applies regardless of thebreadth of the range.

Certain embodiments can also be described broadly and genericallyherein. Each of the narrower species and sub-generic groupings fallingwithin the generic disclosure also form part of the disclosure. Thisincludes the generic description of the embodiments with a proviso ornegative limitation removing any subject matter from the genus,regardless of whether or not the excised material is specificallyrecited herein.

The invention has been described broadly and generically herein. Each ofthe narrower species and sub-generic groupings falling within thegeneric disclosure also form part of the invention. This includes thegeneric description of the invention with a proviso or negativelimitation removing any subject matter from the genus, regardless ofwhether or not the excised material is specifically recited herein.

Other embodiments are within the following claims and non-limitingexamples. In addition, where features or aspects of the invention aredescribed in terms of Markush groups, those skilled in the art willrecognize that the invention is also thereby described in terms of anyindividual member or subgroup of members of the Markush group.

EXPERIMENTAL SECTION

The following examples illustrate methods by which aspects of theinvention may be practiced or materials that may be prepared which issuitable for the practice of certain embodiments of the invention.

Example 1—Materials and Methods Patient Information

Fresh—frozen normal—tumour tissues were obtained from nephrectomy casesunder approvals from institutional research ethics review committees andpatient consent. Normal tissues were harvested from sites distant fromthe tumour. Table 1 refers to detailed patient information of thisstudy.

TABLE 1 Patient information Age at the Fuhrman time of Nuclear IDdiagnosis Race Sex Histo Type Grade 74575859 80 Chinese Female Clearcell carcinoma Grade II 17621953 48 Chinese Male Clear cell carcinomaGrade II 57398667 56 Chinese Male Clear cell carcinoma Grade III70528835 52 Chinese Male Clear cell carcinoma Grade III 77972083 50Chinese Male Clear cell carcinoma Grade IV 75416923 49 Unknown MaleClear cell carcinoma Grade II 20431713 65 Indian Male Clear cellcarcinoma with Grade IV pappilary features 40911432 56 Chinese FemaleClear cell carcinoma Grade II 12364284 Unknown Unknown Unknown Clearcell carcinoma Grade III 86049102 51 Chinese Male Clear cell carcinomaGrade II

Cell Lines

Commercial cell lines (786-O, A-498, HK2, and PCS-400) were purchasedfrom ATCC. Cell lines were maintained in RPMI (Invitrogen) with 10% FBSwith the exception of primary renal proximal tubule epithelial cells,PCS-400, which were maintained in Renal Epithelial Cell Basal Medium(ATCC). Cell line authentication was performed by short tandem repeat(STR) analysis against publicly available STR profiles. Mycoplasmatesting was performed using the MycoSensor PCR assay kit (Stratagene).

Establishment of Tumour-Derived Cell Lines from Primary Tumours

Tumour cells were disassociated from primary tumours by collagenase,seeded, and maintained in RPMI with 10% FBS. At 80% to 90% confluency,the cells were passaged at a ratio of 1:3. Cultured cells wereconsidered to be successfully immortalized after 60 passages. Correctpairing of tumour tissues and cell lines was achieved by comparing thepercentage identity of single nucleotide polymorphisms (SNP) based ontargeted sequencing. All tumour-cell line pairs showed identitiesof >90% whereas shuffling of pairing showed identities <80%. Tumours andcell lines from 12364284 and 40911432 showed the same von Hippel-Lindau(VHL) mutations, but tissue from 86049102 (86049102T) is VHL-mutant,whereas the cognate 86049102 cell line (86049102L) is VHL-wild-type.

Stable Von Hippel-Lindau Restoration in Clear Cell Renal Cell CarcinomaLines

786-O cells (WT2, VHL+) and 786-O cells (RC3, VHL−) were used. Stabletransduction of von Hippel-Lindau (VHL) was performed in A-498,12364284, and 40911432 cells as follows: HA-VHL wt-pBabe-puro plasmidwas transfected into PlatA cells (RV-102, Cell Biolabs) at 2 μg DNA/wellof a 6-well plate using Lipofectamine 3000 (LifeTechnologies). A mediumchange was performed 10 to 16 hours after transfection. The supernatantfrom PlatA cells containing retroviruses was harvested 48 hours laterand added to clear cell renal cell carcinoma cells, which were thenselected with puromycin for 3 days after transduction.

Histone Nano-Chromatin Immunoprecipitation Sequencing (Nano-ChIP-Seq)

Nano-ChIP-seq was performed as previously described with slightmodifications. Fresh-frozen cancer and normal tissues were dissectedusing a razor blade to obtain about 5 mg of tissue. The tissues werefixed in 1% formaldehyde for 10 minutes at room temperature. Fixationwas stopped by addition of glycine to a final concentration of 125nmol/L. Tissue pieces were washed three times with TBSE buffer.Pulverized tissues were lysed in 100 μL lysis buffer and sonicated for16 cycles (30 s on, 30 s off) using a Bioruptor (Diagenode). Thefollowing antibodies were used: H3K27ac (ab4729, Abcam), H3K4me3(07-473, Millipore), H3K4me1 (ab8895, Abcam), and H3K27me3 (07-449,Millipore). The total volume of immunoprecipitation was 1 mL and theamount of antibody used was 2 μg. The input DNA was precleared withprotein G Dynabeads (Life Technologies) for 1 hour at 4° C. and thenincubated with antibodies conjugated protein G beads overnight at 4° C.The beads were washed 3 times with cold wash buffer. After recovery ofchromatin immunoprecipitation (ChIP) and input DNA, whole-genomeamplification was performed using the WGA4 kit (Sigma-Aldrich) andBpmI-WGA primers. Amplified DNA was digested with BpmI [New EnglandBiolabs (NEB)]. After that, 30 ng of the amplified DNA was used with theNEBNext ChIP-seq library prep reagent set (NEB). Chromatinimmunoprecipitation sequencing (ChIP-seq) in cell lines was performedusing the same Nano-ChIP-seq protocol described above but with 1×10⁶cells. Each library was sequenced to an average depth of 20 to 30million raw reads on HiSeq2500 using 101-bp single end reads.

Histone Chromatin Immunoprecipitation Sequencing (ChIP-Seq) Analysis

Sequencing tags were mapped against the human reference genome (hg19)using Burrows-Wheeler Aligner (BWA-mem; version 0.7.10). Reads weretrimmed 10 bp from the front and the back to produce 81 bp. Only readswith mapQ >10 and with duplicates removed by rmdup were used forsubsequent analysis. Significant peaks were called using CCAT (P<0.05).The strength and quality of immunoprecipitation were assessed usingCHANCE.

Transcription Factor Chromatin Immunoprecipitation Sequencing (ChIP-Seq)

For each transcription factor, 3×10⁷ cells were cross-linked with 1%formaldehyde for 10 minutes at room temperature and stopped by addingglycine to a final concentration of 125 nmol/L. Chromatin was extractedand sonicated to about 500 bp (Vibra cell, SONICS). The followingantibodies were used for chromatin immunoprecipitation: c-Jun (sc-1694,Santa Cruz Biotechnology), NF-κB p65 (sc-372, Santa Cruz Biotechnology),ETS1 (sc-350, Santa Cruz Biotechnology), HIF1α (610959, BD Biosciences),HIF2α (NB100-122, Novus Bio), and p300 (sc-585, Santa CruzBiotechnology). The total volume of immunoprecipitation was 1.5 mL andthe amount of antibody used was 15 μg. Input DNAs were precleared withprotein G Dynabeads (LifeTechnologies) for 2 hours at 4° C. and thenincubated with antibody-conjugated protein G beads overnight at 4° C.The beads were washed 6 times with wash buffer at room temperature. Atleast 10 ng of the DNA was used with the NEBNext ChIP-seq library prepreagent set (NEB). Each library was sequenced to an average depth of 30to 50 million reads on a HiSeq2500 using 101-bp single-end reads.

Transcription Factor Chromatin Immunoprecipitation Sequencing (Chip-Seq)Analysis

Sequencing tags were mapped against the human reference genome (hg19)using Burrows-Wheeler Aligner (BWA-mem) (version 0.7.10). Only readswith mapQ >10 and with duplicates removed by rmdup were used in thesubsequent analysis. Significant peaks were called using MACS2 (q-value<0.01). Fastq files of HIF2α ChIP-seq (GSM856790), HIF1β ChIP-seq(GSM856790) and HIF1α ChIP-Seq (GSM1642764) were downloaded from GEOdatabase. Peaks were called using MACS2 using the same settings asabove.

RNA-Seq

Ten pairs of normal-tumour tissue matching the chromatinimmunoprecipitation sequencing (ChIP-seq) tissues were prepared forRNA-seq. Total RNA was extracted using the Qiagen RNeasy Mini kit.RNAseq libraries were prepared using the Illumina Tru-Seq RNA SamplePreparation v2 protocol, according to the manufacturer's instructions.Briefly, poly-A RNAs were recovered from 1 μg of input total RNA usingpoly-T oligo conjugated magnetic beads. The recovered poly-A RNA waschemically fragmented and converted to SuperScript II and randomprimers. The second strand was synthesized using the Second StrandMaster Mix. Libraries were validated with an Agilent Bioanalyzer(Agilent Technologies, Palo Alto, Calif.), diluted to 11 pM and appliedto an Illumina flow cell using the Illumina Cluster Station. Sequencingwas performed on a HiSeq2000 with 74 bp or 76 base pair paired-endreads.

RNA-Seq Analysis

RNA-seq reads were aligned to the human genome (hg19) usingTopHat2-2.0.12 (default parameter and—library-type fr-firststrand). Onlyuniquely mapped reads were analysed. Gene counts were obtained usingHTSeq against the GENCODE v19 reference gene models and subsequentdifferential analysis was performed using DESeq2.

Capture-C

Capture-C was performed as previously described. Briefly, 1×10⁷ cellswere cross-linked by 2% formaldehyde, followed by lysis, homogenization,DpnII digestion, ligation, and de-cross-linking. DNA was sonicated usinga Covaris to 150 to 200 bp to produce DNA suitable for oligo capture. Atotal of 3 pg of sheared DNA was used for sequencing library preparation(NEB). Enhancer sequences were double captured by hybridization tocustomized biotinylated oligos (IDT) and enriched with Dynabeads (LifeTechnologies). Captured DNA was sequenced to an average depth of 2million reads per probe on the HiSeq Illumina platform using 150-bppaired-end reads.

Capture-C Analysis and Gene Assignment

Preprocessing of raw reads was performed to remove adaptor sequences(trim_galore), and overlapping reads were merged using FLASH. In orderto achieve short read mapping to the hg19 reference genome, theresulting preprocessed reads were then in silico digested with DpnII andaligned using Bowtie (using p1, m2, best, and strata settings). Alignedreads were processed using Capture-C analyzer to (i) remove PCRduplicates; (ii) classify subfragments as “capture” if they werecontained within the capture fragment, “proximity exclusion” if theywere within 1 Kb on either side of the capture fragment, or “reporter”if they were outside of the “capture” and “proximity exclusion” regions;and (iii) normalize read counts per 100,000 interactions in bigwigformat. r3Cseq package was used on the capture and reporter fragments toidentify significant interactions of the viewpoint against a scaledbackground (q-value <0.05). Gene assignment is defined by the overlap ofsignificant Capture-C peaks with genes with start and end defined byGENCODE v19. Interactions were plotted using Epigenome Gateway v40.0.

Identification of Differentially Enriched Regions

Significant H3K27ac peaks called by CCAT were merged across allnormal—tumour samples. The same was performed with H3K4me1 and H3K4me3chromatin immunoprecipitation sequencing (ChIP-seq) data. Transcriptionstart sites (TSS) were based on GENCODE v19. Promoters were defined asregions of overlap between H3K27ac and H3K4me3 and also overlapping with±2.0 Kb around the TSS. Enhancers were defined as regions of overlapbetween H3K27ac and H3K4me1 but not overlapping with promoters. Tominimize stromal contamination, we performed further filtering usingcell line data, where enhancers and promoters not overlapping withH3K27ac peaks in any of the cell lines were discarded. Wiggle files ofwindow size 50 bp were generated using MEDIPs from bam files. The inputsubtracted signal for each promoter or enhancer region was computedusing bigWigAverageOverBed to yield reads per kilobase per million(RPKM). The RPKM of H3K27ac, H3K4me1, and H3K4me3 chromatinimmunoprecipitation sequencing (ChIP-seq) from promoters and enhancerswere corrected for batch effects using Combat. Tumour-specific regionswere defined as regions that have a fold difference of and a differenceof 0.5 RPKM from patient matched normal tissue. Normal regions weredefined as regions that have a fold difference of 0.5, and a differenceof −0.5 RPKM from the corresponding regions in patient-matched tumours.Recurrently gained regions were defined as gain in 5/10 patients and noloss in any patients. Recurrently lost regions were defined as loss in5/10 patients and no gain in any patients. Statistical testing for eachcis regulatory region was performed using paired t tests withBenjamini-Hochberg correction. The differential regions were visualizedusing NGSplot.

Identification of Superenhancer Regions

Superenhancer regions were identified using ROSE (with promoterexcluded), using H3K27ac peak regions merged from all patients (bothnormal and tumour tissue). Wiggle files of window size 50 bp weregenerated using MEDIPs from bam files. The input-subtracted signal foreach superenhancer was computed using bigWigAverageOverBed (sum of readsover covered bases). The superenhancer regions were ranked by theaverage difference of normal-tumour H3K27ac chromatinimmunoprecipitation sequencing (ChIP-seq) signals. Gained superenhancerswere defined as regions that have average differential H3K27ac ChIPseqsignals >0. Lost superenhancers were defined as regions that haveaverage differential H3K27ac ChIP-seq signals <0.

Targeted Sequencing

Ten pairs of normal-tumour tissue matching the chromatinimmunoprecipitation sequencing (ChIP-seq) tissues were prepared fortargeted mutation sequencing. Genomic DNA was extracted using the QIAampDNA Mini Kit. Genomic DNA libraries were prepared using KAPA Hyper PrepKit, according to the manufacturer's instructions. Briefly, genomic DNAwas fragmented to 150-200 bp by sonication using a Covaris E-220 FocusedUltrasonicator (Duty Factor: 10%, Cycles per Burst: 200, Treatment Time:360; Covaris Inc.). After the fragmentation process, end-repair,A-tailing, adapter ligation, and PCR reactions before target enrichmentwas performed, following the manufacturer's recommended protocols. Aftereach step, the purification step was performed with AMPure XP beads toremove short fragments such as adapter dimers. Enrichment was performedusing SureSelect XT2 Xplora RNA Bait (Custom, 5.9 Mb). Sequencing wasperformed on a Hiseq2500 with the paired-end 100 bp option.

Principal Component Analysis (PCA)

RPKM values of H3K27ac intensities of all the cis-regulatory elementswere first corrected for batch effects using COMBAT. PCA was performedon the entire 17,497 promoters or entire 66,448 enhancers. Variances andthe cumulative proportion of each principal component were computedusing R.

Saturation Analyses

Saturation analyses were performed independently for enhancers andpromoters. Specifically, subsets of the H3K27ac profiles from 20 primarysamples (consisting of 10 primary tumours and matched normal samples)were selected. All combinations in each subset size were tested exceptthose subsets with >10,000 possible combinations (n=5-15 samples), inwhich case 10,000 randomly selected combinations were tested. Then,H3K27ac enriched regions from each subset were combined, and overlappingregions were merged. These unique regions were then further classifiedas promoters and enhancers using the definitions reported in“Identification of differentially enriched regions”.

GREAT Analysis

Altered promoters were assigned using GREAT v3.0 by the nearest singlegene. Altered enhancers were assigned to the genes with a proximal 5.0Kb upstream, 1.0 Kb downstream extension and a distal extension up to1000 Kb using default GREAT settings. The top pathways enriched in theMSigDB Pathways and Gene Ontology (GO) Molecular Functions were rankedby their hypergeometric q-values.

Epigenome Roadmap Datasets

The bed files from H3K27ac, H3K4me1 and H3K4me3 chromatinimmunoprecipitation sequencing (ChIP-Seq) of two normal kidneys weregenerated by the Epigenome Road. Peaks were identified using COAT.Similarities between the Epigenome Roadmap and our ChIP-Seq data werecomputed by the percentage of overlap between peaks.

DNA Methylation Analysis

In total, 160 tumour-normal matched pairs were obtained from The CancerGenome Atlas (TOGA) database. Quantile normalization was performedacross all the samples. Probes were assigned to the nearest promoter orenhancer with a maximal cutoff of 10 kb.

Chromatin Accessibility Analysis

Bigwig-formatted files of 7 clear cell renal cell carcinoma matchednormal-tumour FAIRE-Seq datasets obtained from EMBL-EBI ArrayExpressunder accession number E-MTAB-1936. FAIRE-Seq signals for each promoteror enhancer region were computed using bigWigAverageOverBed with thepromoters and enhancer regions as the input bed file. FAIRE-Seq data wasnormalized for batch effects using Combat.

lncRNA Analysis

A list of differentially expressed lncRNA in kidney cancer wasdownloaded from a previous study. RPKM values of each lncRNA werecomputed across the same ten pairs of normal-matched tissue wherechromatin immunoprecipitation sequencing (ChIPseq) was performed, usingbigWigAverageOverBed with chromosome positions defined by a previousstudy. These differentially expressed lncRNA were assigned to thenearest promoter and enhancer but with a maximum distance cut off of 10Kb. In total, around 200 lncRNAs were assigned to a promoter or anenhancer.

Motif Analysis

Motif analysis was performed using HOMER using the gained promoters andenhancers as the input regions and lost promoters and enhancers as thebackground. The input regions covered the entire span of promoters andenhancers. For von Hippel-Lindau (VHL)-responsive regions, input regionswere gained enhancers with H3K27ac depletion after VHL restoration andbackground regions were gained enhancers with H3K27ac enrichment afterVHL restoration. Only known motifs were considered.

Histone Chromatin Immunoprecipitation Sequencing (ChIP-Seq) with VonHippel-Lindau Restoration

H3K27ac, H3K4me1 and H3K27me3 ChIP-seq were performed using histoneChIP-seq. Sonicated DNA was normalized for each pair of cells with andwithout wild-type von Hippel-Lindau (VHL) before immuno-precipitation.Differential analysis of H3K27ac was performed using Deseq2 using rawcounts of H3K27ac ChIP-seq with p-value <0.05.

The Cancer Genome Atlas (TCGA) RNA-Seq

Preprocessed RNA-seq v2 data level 3 of clear cell renal cell carcinoma,papillary and chromophobe renal cell carcinoma was downloaded from TCGA.Only patients with matched normal-tumour pairs (72 clear cell renal cellcarcinoma pairs, 32 papillary renal cell carcinoma pairs and 25chromophobe renal cell carcinoma pairs) were considered. The overalltumour-normal ratio of a given gene was computed from averagingindividual tumour-normal ratios, and p-values computed by paired t-test.Pan-cancer compilation of TCGA data was obtained from pancan12.

Immunoblotting

Cell lines were harvested with cold RIPA lysis buffer (50 mM Tris pH 8,150 mM NaCl, 0.1% Triton X-100, 0.5% Sodium deoxycholate, 0.1% SDS) withprotease inhibitors (Roche) on ice. Cells were mechanically lysed bypassing through a 25 Gauge needle and centrifuged at 13,000 rpm for 15min at 4° C. Protein concentrations were measured by the Pierce BCAprotein assay (Life Technologies). Cell lysates were heated at 70° C.for 10 min in sample buffer. Per well, 15 pg of cell lysate was loadedand gel electrophoresis was run at 130V constant for 90 minutes.Proteins were transferred to nitrocellulose membranes by transferring at100 V for 100 minutes in ice. Western blotting was performed byincubating membranes overnight at 4° C. with the following antibodiesand dilutions: ZNF395 (1 pg/ml), von Hippel-Lindau (VHL) (1:250dilution, Cell Signaling 2738), HIF1A (1:500 dilution, BD #610959),HIF1B (1:2000 dilution, Novus Bio NB100-110), HIF2A (1:1000 dilution,Novus Bio NB100-122), ETS1 (1:1000 dilution, Santa Cruz sc-350), c-Fos(1:500 dilution, Santa Cruz sc-7202), c-Jun (1:500 dilution, Santa Cruzsc-1694), NFκB p65 (ab7970, AbCAM) and β-actin (1:2000, Santa Cruzsc-47779). Membranes were incubated in secondary antibodies at 1:10,000dilution for 1 hr at room temperature and developed with SuperSignalWest Femto Maximum Sensitivity Substrate (Thermo Scientific).

siRNA Knockdown

ON-TARGETplus SMARTpool siRNA (Dharmacon, UK) were used withNon-Targeting Control Pool as negative control and GAPDH Control Pool aspositive control. The sequences of the SMARTpool siRNAs were as follows:

HIF2α (EPAS1) (SEQ ID NO: 1 GGCAGCACCUCACAUUUGA, SEQ ID NO: 2GAGCGCAAAUGUACCCAAU, SEQ ID NO: 3 GACAAGGUCUGCAAAGGGU, SEQ ID NO: 4GCAAAGACAUGUCCACAGA) SMDPL3A (SEQ ID NO: 5 CAGUAUGAUCCUCGUGAUU,SEQ ID NO: 6 GAAGAUUUGCAGCCGGAAA, SEQ ID NO: 7 GACAGUAAGCAGUUUAUAA,SEQ ID NO: 8 CGGCCCAAAUAUAAUGACA) ZNF395 (SEQ ID NO: 9CCAAACUGAUCAUGGCUUU, SEQ ID NO: 10 UCAGGCAGAUCAUGCAUAC, SEQ ID NO: 11GUUCUGCGCUCCAUUGUGG, SEQ ID NO: 12 GGACGAACCAGCUCCACGA)

A-498, 786-O and 12364284 and cells were trypsinized and diluted toappropriate concentrations. Lipofectamine RNAiMAX (Life Technologies)and SMARTpool siRNAs were diluted in Opti-MEM to a final siRNAconcentration of 50 nM. The diluted Lipofectamine RNAiMAX was added tothe diluted siRNA and incubated for 15 min at room temperature to allowcomplex formation to occur. The siRNA mixtures were aliquoted to wellsin a 6-well plate. 48 hours after transfection, cells were re-seededinto 6-well plates for colony formation assays and 96-well plates forcell viability assay.

shRNA Knockdown

Lentiviral plasmids were transfected into HEK293T cells. MISSION shRNAclones against ZNF395 were purchased from Sigma Aldrich. The sequencesof the clones are as follows:

TRCN0000233231 SEQ ID NO: 13 CCGGGCATCAAACGACACGTCAAAGCTCGAGCTTTGACGTGTCGTTTGATGCTTTTTG TRCN0000233234 SEQ ID NO: 14CCGGCAGAAGCCTTTACTGATTAAACTCG AGTTTAATCAGTAAAGGCTTCTGTTTTTG

Cells were transduced with lentiviral particles for 48 hours andselected with puromycin (2 pg/ml) for four days before being analyzedfor gene and protein expression and other functional assays.

Quantitative PCR Analysis (qPCR)

Total RNA was extracted from cell lines using Trizol (ThermoFisher) andpurified with the RNeasy Mini Kit (Qiagen). Reverse transcription wasperformed using iScript Reverse Transcription Supermix for RT-qPCR(Biorad). qPCR was performed using Taqman probes (ZNF395 Assay ID:Hs00608626_m1, SMPDL3A Assay ID: Hs00378308_m1) with TaqMan GeneExpression Master Mix (Thermo Fisher). Gene expression changes werenormalized to GAPDH (Assay ID: Hs00699446_m1).

Chromatin Immunoprecipitation Quantitative Polymerase Chain Reaction(ChIP-qPCR)

ChIP DNA was probed with the following primers using the SYBR qPCRmaster mix (ThermoFisher).

ZNF395-E1 (hg19 chr8: 28221378-28221459) ZNF395-E1-F: (SEQ ID NO: 15)GCAACCTTCCAGGCCTGCCG ZNF395-E1-R: (SEQ ID NO: 16) AGGAGAAAGGGGACAGGAGGGCZNF395-E2 (hg19 chr8: 28222803-28222908) ZNF395-E2-F: (SEQ ID NO: 17)TGGGCCGCCCGTGACTTTTC ZNF395-E2-R: (SEQ ID NO: 18) GGTTGGAAGGAGGCCACCGCZNF395-E3 (hg19 chr8: 28223142-28223230) ZNF395-E3-F: (SEQ ID NO: 19)TCGTGCTGAAGGCTTCTCAGGAAA ZNF395-E3-R: (SEQ ID NO: 20)CCCCTCCTGTTGGTGACGGC ZNF395-E4 (hg19 chr8: 28269095-28269211)ZNF395-E4-F: (SEQ ID NO: 21) AAGCGGCGGGAGGAGGTTGA ZNF395-E4-R:(SEQ ID NO: 22) GGGCTGCGTCACCTGCAGAA

Luciferase Assay

Genomic DNA from where 786-O cells were extracted using DNeasy Blood &Tissue Kit (Qiagen). Regions corresponding to putative enhancers wereamplified using CloneAmp HiFi PCR Premix (Clonetech) and cloned into thepGL3 luciferase reporter vector with a minimal FOS promoter.

Forward primer: (SEQ ID NO: 23)GTAGCTGCATAGATCTGCGCGCCACCCCTCTGGCGCCACCGT Reverse_primer:(SEQ ID NO: 24) GTAGCTGCATCAAGCTTGCCGGCTCAGTCTTGGCTTCTC

The day prior to transfection, 1×10⁴ cells were seeded into each well ofa 96-well plate. Cells were transfected with 100 ng of pGL3-Fos-enhancerand 20 ng of pRL-SV40 (Renilla luciferase vector, Promega). Cells werelysed and analyzed using the Dual-Luciferase Reporter System (Promega).Primer sequences used to amplify genomic regions for luciferase reporterassays are as follows:

VEGFA-E1 (hg19 chr6: 43635485-43636708) VEGFA-E1-F_Mlul: (SEQ ID NO: 25)GCTCTTACGCGT TGGGGGTGCCTCTCCCACTG VEGFA-E1-R_Nhel: (SEQ ID NO: 26)GCCCGGGCTAGC GGGTGGGGGTCCAACAGGACAVEGFA-E2 (hg19 chr6: 43692413-43693560) VEGFA-E2-F_Mlul: (SEQ ID NO: 27)GCTCTTACGCGT CCCATCCCCTGCCTCCTGCT VEGFA-E2-R_Nhel: (SEQ ID NO: 28)GCCCGGGCTAGC TGGGCTGGCTGCAAAGTGGCSLC2A1-E1 (hg19 chr1: 43523259-43525686) SLC2A1-E1_F_Mlul:(SEQ ID NO: 29) GCTCTTACGCGT TGGTGACCGTGTTGGGGGTGA SLC2A1-E1_R_Nhel:(SEQ ID NO: 30) GCCCGGGCTAGC TCCCCGCCCCTCTGTTGCATZNF395-E1 (hg19 chr8: 28220788-28221483) ZNF395-E1-F_Mlul:(SEQ ID NO: 31) GCTCTTACGCGT ACAGGTGTGCGCTACCACGC ZNF395-E1-R_Nhel:(SEQ ID NO: 32) GCCCGGGCTAGCTGGTGTGGAATTCTGGCCAGTTAAAGGZNF395-E2 (hg19 chr8: 28221957-28222965) ZNF395-E2-F_Mlul:(SEQ ID NO: 33) GCTCTTACGCGT TCGGGAGGTTCAAGACCAGCCT ZNF395-E2-R_Nhel:(SEQ ID NO: 34) GCCCGGGCTAGCGCTCCCAAGAAAGAACTTACCAGAGGZNF395-E3 (hg19 chr8: 28222984-28224154) ZNF395-E3-F_Mlul:(SEQ ID NO: 35) GCTCTTACGCGT ACCAGCCATCCCCTAGTTTGCC ZNF395-E3-R_Nhel:(SEQ ID NO: 36) GCCCGGGCTAGC GGCATTTGTCAGCAGAGATGTTGGC

Colony Formation and Cell Viability Assays

For colony formation assays, 5000 cells per condition were seeded into 6well dishes and were allowed to grow for 12 days. Colonies were stainedwith 0.05% Crystal Violet. For cell viability assay, 1000 cells percondition were seeded into 96-well plate and the cell viability wasmeasured by CellTiter-Glo Luminescent Cell Viability Assay (Promega) for5 days.

Apoptosis Assay

For each condition, 1×10³ cells were seeded into each well of a 96-wellplate. Caspase3/7 activity was measured with the cleavage ofproluminescent caspase-3/7 substrate after 1 hour incubation usingCaspase-Glo® 3/7 Assay (Promega). Alternatively, cells were stained withFITC Annexin V Apoptosis Detection Kit (BD Bioscences) and Calcein AM(ThermoFisher) and analyzed on a flow cytometer.

In Vivo Studies

All animal studies were conducted in compliance with animal protocolsapproved by Institutional Animal Care and Use Committee (IACUC) ofSingapore. Female NOD/SCID mice (6-8 week old) were implanted with 1×10⁶A-498 or 1×10⁶ 786-O cells transduced with either empty vector controlor shRNA clones subcutaneously in the flank. Tumour volume was monitoredevery 2 to 3 days. Tumour volume was calculated as(length×width×width)×π/6. Animals were sacrificed when the tumour volumeexceeded 1000 mm³.

CRISPR-Mediated Enhancer Deletion

To delete enhancer regions, 2 gRNAs (left and right) were used to cleavetargeted regions as previously described. gRNAs were designed with ATUMgRNA Design Tool. Briefly, phosphorylated and annealed sense andantisense oligos were ligated into BpiI digested vectors. Left gRNAswere cloned into the BpiI digested pX330A-2A-GFP-1X2 backbone (Addgene#58766) whereas the right gRNAs into BpiI digested pX330S backbone(Addgene #58778). Golden gate assembly was performed to assemble the 2gRNA protospacers into the pX330A-2A-GFP-1X2 plasmid backbone using aone-step digestion and ligation with slight modifications. Aftertransfection using Lipofectamine 3000 (Life Technologies), GFP-positivesingle 786-O cells were sorted and cultured. Individual clones werevalidated for enhancer deletion by PCR of genomic DNA and the resultinggene expression was measured using qPCR and Taqman probes. Clones thatwere transfected with gRNAs but failed to have enhancer deletions wereused as negative controls. The gRNAs used for deletion of enhancers areas follows:

ZNF395_E3 (hg19 chr8: 28223203-28224208) ZNF395_E3_L_F_gRNA:(SEQ ID NO: 37) CACCGTCCCTACTGCCGTCACCAAC ZNF395_E3_L_R_gRNA:(SEQ ID NO: 38) AAACGTTGGTGACGGCAGTAGGGAC ZNF395_E3_R_F_gRNA:(SEQ ID NO: 39) CACCGAAATATGTTTATGGTCCTCC ZNF395_E3_R_R_gRNA:(SEQ ID NO: 40) AAACGGAGGACCATAAACATATTTC

Validation Primers for Deletion of Enhancers:

ZNF395-E3 (Product size after deletion: 293bp; WT: 1299bp) ZNF395-E3-F:(SEQ ID NO: 41) ACCAGCCATCCCCTAGTTTGCCA ZNF395-E3-R: (SEQ ID NO: 42)GCCACCAGGTAGCAGTTGGGT

Date Accession

Chromatin immunoprecipitation sequencing (ChIP-seq) and RNAseq data areavailable at Gene Expression Omnibus (GSE86095).

Example 2—Cis-Regulatory Landscapes in Clear Cell Renal Cell CarcinomaTumours are Aberrant

To explore whether clear cell renal cell carcinoma tumours displayalterations in their cis-regulatory landscapes in vivo, histonechromatin immunoprecipitation sequencing (ChIP-seq) profiles (3 marks:H3K27ac, H3K4me3, and H3K4me1) were generated in 10 primarytumour/normal pairs, 5 patient-matched tumour-derived cell lines, 2commercially available clear cell renal cell carcinoma lines (786-O andA-498), and 2 normal kidney cell lines (HK2 and PCS-400. Table 1 inexample 1 shows patient clinical information. Of the original 87samples, 79 samples passed pre-sequencing quality-control filters andwere subjected to ChIP-seq processing and downstream analysis. In total,2,363,904,778 uniquely mapped reads were generated. On average, 89% ofH3K27ac peaks, 98% of H3K4me3 peaks, and 76% of H3K4me1 peaks obtainedin our normal kidney tissues overlapped with peaks from adult kidneytissues in the Epigenomics Roadmap dataset (FIG. 1A). Among the 10primary clear cell renal cell carcinomas, 9 harbored von Hippel-Lindau(VHL) mutations, detected by targeted sequencing and confirmed by Sangersequencing (Table 2). Cell lines 786-O and A-498 also harbor VHLtruncating mutations (Table 2). The VHL mutations co-occurred withsomatic mutations of other chromatin modifiers commonly found in clearcell renal cell carcinoma, including PBRM1 ( 7/10), SETD2 ( 1/10), KDM5A( 1/10), KDM5C ( 1/10), ARID1A ( 1/10), and KMT2C ( 1/10).

TABLE 2 Clear cell renal cell carcinoma tissue andcell lines von Hippel-Lindau (VHL) mutation confirmation by sequencingSample Muta- amino acid % alt ID tion Chr Position Ref Alt changealleles tissue 12364284 indel chr3 10188261 T TAA Phe136Asn- 42.15fsTer24 tissue 17621953 indel chr3 10183790 GTATGGCTC G Trp88Arg- 14.29AAC fsTer41 tissue 20431713 indel chr3 10191582 AA A Asn193Met- 49.09fsTer201 tissue 40911432 indel chr3 10191500 G GT Val125Cys- 33.05fsTer8 tissue 57398667 indel chr3 10183765 TCGCAGTC T Ser80Ala- 36.11fsTer36 missense chr3 10183754 A G Ile75Val 32.86 tissue 70528835 indelchr3 10183699 C CG Arg58Ala- 77.27 fsTer75 tissue 74575859 missense chr310188320 G A Val155Met 37.9 tissue 77972083 splice chr3 10188195 TAG Tsplice 36.92 acceptor variant tissue 86049102 missense chr3 10183771 TSer80Arg 28.6 tissue 75416923 wt cell 786-O indel chr3 10183840 GG GGly104Ala- 100 line fsTer55 cell A498 indel chr3 10188282 TTGAC TGly144Ser- 93.87 line fsTer14 cell 40911432 indel chr3 10191500 G GTVal125Cys- 92.36 line fsTer8 cell 86049102 missense chr3 10191548 G AVal140Ile 2.61 line cell 12364284 indel chr3 10188261 T TAA Phe136Asn-93.17 line fsTer24

Specific histone modifications can distinguish different categories offunctional regulatory elements—H3K4me3 is generally associated withpromoters, H3K4me1 with enhancers, and H3K27ac with active elements.Integrating signals from three histone marks and GENCODE v19 annotatedtranscription start sites (TSS), active promoters were defined asH3K27ac⁺/H3K4me3⁺/±2.0 kb TSS regions, and distal enhancers asH3K27ac⁺/H3K4me1⁺ regions not overlapping with promoters. Focusing onepigenomic events specific to somatic cancer cells, cell lines werederived from five primary tumours and, combined with the commerciallines, excluded peaks not found in any of the cell lines to reduceconfounding effects from stromal cells. On average, 80% overlap ofchromatin immunoprecipitation sequencing (ChIP-seq) peaks was observedbetween primary tumours and matched lines (FIG. 1B). Using thesecriteria, 17,497 putative promoters and 66,448 putative enhancers (FIG.10 ) were identified, with numbers comparable with previous studies inother tumour types. The numbers of defined promoters and enhancersreached saturation after 4 and 16 samples, respectively, suggesting thata sample size of 20 (10 tumour/normal pairs) is sufficiently powered todiscover the majority of cis-regulatory elements in clear cell renalcell carcinoma (FIG. 1E). Principal components analysis (PCA) using thefirst two components of global H3K27ac intensities at promoters orenhancers (representing 83% and 64% of total variance, respectively;FIG. 1F) successfully separated normal and tumour samples, indicatingthat genome-wide pervasive alterations in cis-regulatory elements are asalient feature of clear cell renal cell carcinoma (FIG. 1D).

Differential analysis was performed to identify altered promoters andenhancers. To define gained or lost regions, a fold difference ofH3K27ac RPKM ≥2, an absolute difference 0.5, and for greater stringencyno alterations in the reverse direction in the remaining tumour/normalpairs was applied (FIG. 1G). At the threshold of ≥ 5/10 patients, 80% ofthe altered regions achieved statistical significance (q-value <0.1,paired t test, with Benjamini-Hochberg correction; FIG. 1H), and at thissame threshold, the increase in the fraction of samples meetingstatistical significance reached a saddle point (FIG. 1I). Applyingthese criteria, a high-confidence and comprehensive set of 4,719 gainedpromoters, 592 lost promoters, 4,906 gained enhancers, and 5,654 lostenhancers was obtained (FIG. 10 , FIG. 1J). Representative regions arepresented in FIG. 1K (FIGS. 1Ki and 1Kii).

Supporting these data, gained promoters and enhancers exhibitedincreased chromatin accessibility measured by higher FAIRE-seq signalsin tumour tissues than normal tissues, respectively (P<0.0001) and alsodecreased DNA methylation based on data from The Cancer Genome Atlas(TCGA), consistent with reciprocal relationships between activeregulatory regions and DNA methylation (FIG. 1L). Interestingly,elevated expression of long noncoding RNAs adjacent to gained promotersand enhancers was noted in tumour tissues compared with normal tissues(P<0.0001, respectively). Lastly, many of the cis-regulatory elementswere confirmed to involve regions previously implicated in clear cellrenal cell carcinoma; for example, gains of H3K27ac signals andenrichment of H3K4me1 at a distal enhancer of CCND1 overlapping with arenal cell carcinoma susceptibility locus (rs7105934; FIG. 1M) wasobserved. The ability to identify this previously known enhancer withunbiased profiling further supports the method of this study.

Example 3—Tumour-Specific Enhancers are Associated with Hallmarks ofClear Cell Renal Cell Carcinoma

To identify genes modulated by the tumour-specific regulatory elements,enhancers were assigned using three approaches. The first approachutilized predefined linear proximity rules involving a set of highlyconfident genes (GREAT algorithm). MSigDB pathway analysis usingGREAT-assigned genes revealed that gained enhancers exhibit a highlysignificant renal cell carcinoma-specific signature compared with gainedpromoters (enhancer q-value=3.2×10⁻²⁶; promoter q-value=1.5×10⁻¹,binomial FDR; FIG. 2A). Although gained promoters were involved ingeneral cancer processes (for example, cell cycle, transcription, andRNA metabolism) for a complete list of promoter pathways), gainedenhancers were enriched in disease-specific features of clear cell renalcell carcinoma, including HIF1α network activity, proangiogenic pathways(platelet activation and PDGFRβ signaling), and SLC-mediatedtransmembrane transport (FIG. 2A) for a complete list of enhancerpathways). Notably, HIF1α network activity consistently emerged as oneof the top five pathways, even with perturbations in the patientthresholds used to define gained enhancers (≥3-8 patients; Table 3).

TABLE 3 HIF pathway as the top pathway with patient thresholds. FDRstand for false discovery rate. Binomial FDR Binomial Cut-offs Rank FDR≥3 1 2.50E−31 ≥4 3 7.90E−28 ≥5 1 9.20E−30 ≥6 1 1.50E−25 ≥7 1 2.70E−18 ≥84 3.30E−18

Individual genes associated with gained enhancers included well-knownhypoxic targets (VEGFA, FIG. 2B; CXCR4) and metabolic genes involved inglycolysis, glutamine intake, and lipid storage (GLUT1/SLC2A1, FIG. 2C;HK2, PFKFB3, PLIN2, FIG. 2D) and SLC38A1 (FIG. 2E). The presence ofenhancers around metabolic enzymes and transporters is largelyconsistent with the metabolic contexture of clear cell renal cellcarcinoma, which involves increased glycolysis and glutaminolysis.Indeed, gene ontology (GO) analysis of gained enhancers stronglyreflected hallmark metabolic changes associated with clear cell renalcell carcinoma, including monocarboxylic acid transmembrane transporteractivity (binomial FDR q-value=1.6×10⁻¹⁰; FIG. 2F).

A second method of enhancer-gene assignment based on correlationsbetween H3K27ac signals and expression of genes within the sametopologic associated domain (TAD). Using a q-value of <0.05 based onSpearman correlation, 2,311 gained enhancers were assigned to 2,186protein-coding targets. H3K27ac signals of many gained enhancers werehighly correlated with gene expression of their putative target genes.For example, H3K27ac levels of a VEGFA enhancer exhibited highcorrelation with VEGFA gene expression (r=0.83, Spearman correlation),whereas H3K27ac signals of an SLC2A1 enhancer were highly correlatedwith SLC2A1 gene expression (r=0.72, Spearman correlation; FIG. 2B; FIG.2G). Similar to the GREAT approach, the TAD correlation approach alsohighlighted hypoxia (Krieg_Hypoxia_not_via_KDM3A, FDR q-value=7×10⁻¹²⁰)and metabolism (Chen_Metabolic_Syndrome_Network, FDR q-value=2×10⁻⁹¹) ashighly enriched pathways (Table 4).

TABLE 4 Highly enriched pathways of TAD correlation approach # Genes inGene Set Gene Set Name (K) Description KRIEG_HYPOXIA_NOT_VIA_KDM3A 770Genes induced under hypoxia independently of KDM3A [GeneID = 55818] inRCC4 cells (renal carcinoma) expressing VHL [GeneID = 7428].PILON_KLF1_TARGETS_DN 1972 Genes down-regulated in erythroid progenitorcells from fetal livers of E13.5 embryos with KLF1 [GeneID = 10661]knockout compared to those from the wild type embryos.PUJANA_ATM_PCC_NETWORK 1442 Genes constituting the ATM-PCC network oftranscripts whose expression positively correlated (Pearson correlationcoefficient, PCC >= 0.4) with that of ATM [GeneID = 472] across acompendium of normal tissues. CHEN_METABOLIC_SYNDROM_NETWORK 1210 Genesforming the macrophage-enriched metabolic network (MEMN) claimed to havea causal relationship with the metabolic syndrom traits.BLALOCK_ALZHEIMERS_DISEASE_UP 1691 Genes up-regulated in brain frompatients with Alzheimer's disease. RODWELL_AGING_KIDNEY_UP 487 Geneswhose expression increases with age in normal kidney.PUJANA_BRCA1_PCC_NETWORK 1652 Genes constituting the BRCA1-PCC networkof transcripts whose expression positively correlated (Pearsoncorrelation coefficient, PCC >= 0.4) with that of BRCA1 [GeneID = 672]across a compendium of normal tissues. DODD_NASOPHARYNGEAL_CARCINOMA_DN1375 Genes down-regulated in nasopharyngeal carcinoma (NPC) compared tothe normal tissue. MARSON_BOUND_BY_E2F4_ UNSTIMULATED 728 Genes withpromoters bound by E2F4 [GeneID = 1874] in unstimulated hybridoma cells.NUYTTEN_EZH2_TARGETS_UP 1037 Genes up-regulated in PC3 cells (prostatecancer) after knockdown of EZH2 [GeneID = 2146] by RNAi.

Third, to independently validate the GREAT and TAD approaches in thespecific context of clear cell renal cell carcinoma, the interactome ofclear cell renal cell carcinoma tumour-specific enhancers was studied byperforming Capture-C assays. Compared with other chromatin capturetechniques, Capture-C offers both high-resolution (down to single Kbresolution) and high-throughput interrogation of user-defined regions (ausual working range of 10-500 regions). Probes were designed against asubset of 56 gained enhancers and examined their interactions withprotein-coding genes in 786-O cells. Each gene-enhancer pair revealed byCapture-C was further filtered by correlations between gene expressionand H3K27ac levels (q-value <0.05). The 56 gained enhancers were pairedwith 36 protein-coding genes. 58% of these were predicted by GREAT, and80% by gene correlations within TADs. The median distance ofinteractions detected by Capture-C was 16 kb, and 83% of theinteractions fell within a 100-kb window (FIG. 2H). As a visual example,Capture-C confirmed interactions between VEGFA enhancer and the VEGFATSS, spanning a distance of about 100 kb (FIG. 2B), and interactionsbetween the SLC2A1 enhancer and its promoter (FIG. 2C). Takencollectively, these findings highlight the disease-specific nature ofenhancer elements and an important role for enhancer malfunction inmodulating clear cell renal cell carcinoma pathology.

Example 4—Tumour Super-Enhancers Identify ZNF395 as a Master Regulatorof Clear Cell Renal Cell Carcinoma Tumourigenesis

The importance of enhancers in clear cell renal cell carcinoma led tothis study to examine the landscape of “superenhancers” or“stretch-enhancers”—dense clusters of enhancers located near masterregulators of cell identity and disease. Using ROSE, 1,451superenhancers were identified in the clear cell renal cell carcinomacohort, of which 1,157 were gained in tumours and 294 were lost intumours.

Putative targets of top gained superenhancers validated well-knownoncogenes including MYC/PVT1, VEGFA, and HIF2A (FIGS. 3A, 3B and 3C). Inaddition, several less-known genes were found including ERG/C1, ZNF395,SLC28A1, and SMPDL3A (FIG. 3D). These genes were highly overexpressed intumours compared with their matched normal tissues (FIG. 3D).Furthermore, they were unique to clear cell renal cell carcinoma andwere not overexpressed in papillary and chromophobe renal cellcarcinomas, two other distinct clear cell renal cell carcinoma subtypes(FIG. 3D). For instance, ZNF395 exhibited a tumour-normal ratio of about7 in clear cell renal cell carcinoma (P=1×10⁻²², paired t test) butexperienced little overexpression in papillary and chromophobe renalcell carcinoma with tumour-normal ratios of 1.2 and 1.3, respectively(P=0.02 in papillary and P=0.06 in chromophobe, paired t test).

Conversely, genes associated with lost super-enhancers were recurrentlysuppressed in clear cell renal cell carcinoma and included EFHD1, EHF,MAL, GCOM1, and HOXB9 (FIG. 3D). In contrast to the lineage-specificnature of tumour super-enhancers, genes associated with lostsuper-enhancers were common between clear cell renal cell carcinoma andpapillary renal cell carcinoma, implying a more universal function oftumour suppressor genes. For example, EHF/ESE2, a tumour suppressorpreviously found in prostate cancer, exhibited reduced expression acrossall three renal cell carcinoma subtypes (clear cell renal cell carcinomatumour/normal=0.05, P=3×10⁻¹⁵; papillary tumour/normal=0.1, P2×10⁻⁶;chromophobe tumour/normal=0.1, P=2×10⁻⁶)

Since current therapeutic targets in kidney cancer are limited toangiogenesis and mTOR pathways, less-understood genes uncovered bysuperenhancer profiling were examined. ZNF395 and SMPDL3A were chosenfor their differential tumour expression (6-7 tumour-normal ratio; FIG.3D) and high abundance (average RPKM of ZNF395 about 112; average RPKMof SMPDL3A about 58). Even though ZNF395 was previously identified as apotential clear cell renal cell carcinoma biomarker, its functional rolein clear cell renal cell carcinoma malignancy remains unexplored.SMPDL3A shares 31% amino acid identity with the acid sphingomyelinaseSMPD1 and is a target of a master regulator of cholesterol metabolism,liver X receptors (LXR).

Quantitative PCR (FIG. 3E) and immunoblotting (FIG. 3F) confirmed thatA-498 and 786-O clear cell renal cell carcinoma cells exhibited highexpression of ZNF395 and SMPDL3A, whereas normal kidney proximal tubulecells, PCS-400 and HK2, exhibited low expression of both genes. siRNAmediated knockdown of SMPDL3A had a cell line-dependent effect on colonyformation, inhibiting the growth of A-498 cells but having no observableeffect on 786-O cells (FIG. 3G). On the other hand, ZNF395 consistentlyinhibited colony formation in both 786-O and A-498 cells but had minimaleffect on normal kidney cells (FIG. 3G, FIG. 3H). Consistent with thisphenotypic observation, the ZNF395 super-enhancer was active only inclear cell renal cell carcinoma cells (786-O and A-498) but silent innormal kidney cells (HK2 and PCS-400; FIG. 3I). SMPDL3A and SLC28A1(FIG. 3J) are also shown to be associated with a clear cell renal cellcarcinoma-specific super-enhancer. SLC6A3, EGLN3 and VEGFA shows gain inpromoters and enhancers in the tumour sample as compared to the normal(non-diseased) sample (FIGS. 3Ki, 3Kii and 3Kiii). Furthermore, amongthe 33 types of cancer profiled by The Cancer Genome Atlas (TCGA),SMPDL3A (FIG. 3L), SLC28A1 (FIG. 3M), SLC6A3 (FIG. 3N), VEGFA (FIG. 3O),EGLN3 (FIG. 3P), ZNF395 (FIG. 3Q—only 12 cancer types profiled) are alsoshown to be highly expressed in clear cell renal cell carcinoma tumours(KIRC) from The Cancer Genome Atlas (TCGA) data.

No study to date has functionally tested the tumourigenic requirement ofZNF395 in clear cell renal cell carcinoma or any other cancer type.ZNF395's tumour-promoting effect using individual shRNA clones wasvalidated (FIG. 3R, FIG. 3S). Two independent ZNF395 shRNA clonesdrastically decreased in vitro colony formation (FIG. 3T) and cellviability (FIG. 3U) in both A-498 and 786-O cells. ZNF395 knockdown alsoresulted in increased apoptosis measured by cleavage of caspase 3/7substrates (FIG. 3V) and Annexin V staining (FIG. 3W). In vivo, tumourformation studies in mouse xenograft models revealed marked tumoursuppression by ZNF395 depletion (FIG. 3X). Knockdown of ZNF395 led toelimination of A-498 tumours up to day 74, when tumours in the controlgroup began to exceed the size limits imposed by institutional animalprotocols. Similarly, ZNF395 depletion significantly slowed in vivotumour growth of 786-O cells (FIG. 3X). Taken together, the role ZNF395plays in clear cell renal cell carcinoma tumourigenesis was shown.

Example 5—Von Hippel-Lindau (VHL) Deficiency Remodels Clear Cell RenalCell Carcinoma Enhancer Landscapes

To explore the extent to which epigenetic changes observed in primaryclear cell renal cell carcinomas (FIG. 1 ) are directly driven by vonHippel-Lindau (VHL) loss, chromatin changes in isogenic cell lines wereexamined with and without VHL restoration. Consistent with earlierfunctional studies of VHL, VHL restoration in 786-O, A-498, and 12364284cells had negligible effects on proliferation, colony formation, andapoptosis in vitro, but profoundly delayed tumour growth in vivo (FIGS.4A, 4B, 4C and 4D), suggesting the importance of VHL in modulatingprocesses required for in vivo tumourigenesis, including tumour-stromacross-talk, angiogenesis, cell-matrix interactions, or tumourmetabolism.

Focusing on the same regions defined in the primary tumours (4,719gained promoters, 4,906 gained enhancers, and 1,157 gainedsuper-enhancers; FIG. 1C), von Hippel-Lindau (VHL)-driven H3K27acchanges in four different cell lines (two commercial cell lines: 786-Oand A-498; and two patient-derived cell lines: 12364284 and 40911432)was examined. Consistently across all four cell lines, VHL restorationinduced more pronounced changes on enhancers and super-enhancers than onpromoters (FIGS. 4E, 4F, 4G and 4H). For example, in 786-O cells, afterVHL restoration 12% of enhancers (549 enhancers) were significantlydepleted, compared with 6.5% of promoters (321 promoters; FIG. 4E). Thisconfirmed that a greater fraction of enhancers were significantlyaltered by VHL restoration than promoters (P<2.2×10⁻¹⁶, proportionstest), and an even higher proportion involved gained superenhancers(P<2.2×10⁻¹⁶, proportions test).

Even though gained enhancers were expected to show only depletion aftervon Hippel-Lindau (VHL) restoration, changes in H3K27ac levels werebidirectional (FIG. 4E). However, only gained enhancers with H3K27acdepletion were uniquely active in VHL-mutated clear cell renal cellcarcinoma cell lines (786-O, A-498, and 12364284) compared withVHL-wild-type clear cell renal cell carcinoma cells (86049102L), normalkidney cell lines (PCS-400, HK2, and HKC-8), and 31 other cell lines ofvarious cancer types (FIG. 4I). The lack of H3K27ac signals in normalkidney cell lines argues against tissue lineage as the dominantcontributor to the high H3K27ac chromatin immunoprecipitation sequencing(ChIP-seq) signals seen in clear cell renal cell carcinoma cell lines.On the other hand, gained enhancers with H3K27ac enrichment after VHLrestoration showed high activity across multiple cancer types,suggesting that these enhancers are not unique to clear cell renal cellcarcinoma (FIG. 4I).

Furthermore, only gained enhancers showing H3K27ac depletion after vonHippel-Lindau (VHL) restoration were significantly associated with aconcomitant downregulation of gene expression of their putative targetsin both 786-O and 12364284 cells, whereas enhancers gained in primaryclear cell renal cell carcinomas and further H3K27ac enriched after VHLrestoration did not lead to significant gene upregulation on a globallevel (FIG. 4J, FIG. 4K). These results suggest that the formerenhancers (H3K27ac depletion) are likely to represent clear cell renalcell carcinoma—and VHL specific epigenomic alterations, whereas thelatter enhancers (H3K27ac enrichment) are likely to represent signifygeneric, compensatory mechanisms in response to VHL restoration.Combining data from multiple lines, a total of 1,564 enhancers weredepleted by VHL restoration in cell line, representing almost a third(32%) of all gained enhancers identified in primary clear cell renalcell carcinoma tumours. The proportion of VHL responsive enhancersincreased with the level of patient recurrence—only 7.8% of nonrecurrentgained enhancers ( 1/10 patients) showed von Hippel-Lindau(VHL)-mediated H3K27ac depletion, whereas 18% of enhancers recurrentlygained in 9 of 10 patients and 20% of enhancers gained in 10 of 10patients showed H3K27ac depletion in 786-O cells (FIG. 4L, P=0.0001,proportions test), consistent with the high prevalence of VHL mutations( 9/10 patients) in the studies. Interestingly, unsupervised clusteringusing the 1,564 VHL-responsive gained enhancers segregated the singleVHL-wild-type tumour (ID 75416923) away from the remaining 9 VHL-mutanttumours (FIG. 4M), with the VHL-wild-type tumour showing low H3K27acsignals at the ZNF395 superenhancer comparable with its patient-matchednormal (FIG. 4N). Collectively, pathway analysis of enhancers depletedin ≥2 cell lines highlighted direct p53 effectors, integrin-linkedkinase signaling, and HIF1α transcription factor networks as the topfive pathways, covering genes such as EGFR (FIG. 4O), CCND1 (FIG. 4P),ITGB3 (FIG. 4Q), VEGFA (FIG. 4S), SLC2A1 (FIG. 4R), and HK2 (FIG. 4T).These results support a role for VHL loss in clear cell renal cellcarcinoma enhancer malfunction, even in the presence of other drivermutations.

It was also examined whether other histone marks were concomitantlyaltered with H3K27ac marks. A high degree of correlation was foundbetween H3K27ac and H3K4me1 in response to von Hippel-Lindau (VHL)restoration in both 786-O cells (r=0.77, Pearson correlation) and12364284 cells (r=0.61, Pearson correlation) in FIG. 4U. Globally,enhancers exhibiting H3K27ac depletion also experienced concomitantH3K4me1 depletion (FIG. 4W). It was next examined whether VHLrestoration led to acquisition of the H3K27me3 repressive mark. Despitea moderate anticorrelation of H3K27ac and H3K27me3 (786-O cells:r=−0.28, Pearson correlation; 12364284 cells: r=−0.22, Pearsoncorrelation, FIG. 4V), H3K27me3 levels remained low at gained enhancerseven after VHL restoration (FIG. 4W). These findings suggest that VHLrestoration may result in a loss of enhancer identity by codepletion ofH3K27ac and H3K4me1, but not a formal transition to a poised enhancerstate that would have retained H3K4me1 but acquired H3K27me3.

Example 6—HIF2α-HIF1β Heterodimer is Enriched at Von Hippel-Lindau(VHL)-Responsive Enhancers

It was investigated which transcription factors might mediate vonHippel-Lindau (VHL)-dependent chromatin remodeling at gained enhancers.Using the primary clear cell renal cell carcinoma dataset, enrichment oftrans-regulators in gained enhancers over lost enhancers was examined.Using HOMER, it was found that the top enriched motifs were the AP1family, ETS family, and NF-κB-p65-Rel and HIF1α/2α motifs (FIG. 5A). Forsubsequent in vitro validation, c-Jun was chosen as a representative AP1family member because of its activation in clear cell renal cellcarcinoma and ETS1 as an ETS family representative because of its knowninteraction with HIF2a, but acknowledge that other family AP1 and ETSfamily members may play a role in clear cell renal cell carcinoma.Immunoblotting of c-Jun, ETS1, and NF-κB-p65 showed variable proteinexpression in both normal and tumour cell lines, but expression of HIF1αand HIF2α restricted to tumour cells only (FIG. 5B). HIF2α was expressedin a higher proportion of clear cell renal cell carcinoma cell linesthan HIF1α (FIG. 5B). Gene expression of these transcription factors wasfurther examined in the The Cancer Genome Atlas (TCGA) cohort and foundthat ETS1, RELA (subunit of NF-κB-p65), and HIF2α were significantlyoverexpressed in tumours compared with normal tissues, with a range oftumour-association expression patterns similar to variations in clearcell renal cell carcinoma lines (FIG. 5C).

To further investigate chromatin occupancy of these factors, chromatinimmunoprecipitation sequencing (ChIP-seq) binding profiles of c-Jun,ETS1, and NF-κB cells were generated and HIF2α, HIF1α, and HIF1β bindingprofiles from the previous literature were examined in 786-O cells. As786-O cells contain lost endogenous HIF1α expression through genomicdeletion, the HIF1α ChIP-seq was performed on 786-O cells geneticallymanipulated to reexpress HIF1α protein. ChIP-seq results showed that allsix transcription factors exhibited increased occupancy at gainedenhancers compared with lost enhancers, validating the HOMER predictions(FIG. 5D).

To determine which of these transcription factors might be directlydependent on von Hippel-Lindau (VHL), their protein expression was thencompared in VHL-mutated isogenic cell lines with and withoutwild-type—VHL restoration. As shown in FIG. 5E, VHL restorationconsistently downregulated HIF2α expression in both 786-O and 12364284cell lines, but protein levels of other factors displayed contrastingtrends between the two cell lines, implying that among the six factorsexamined, HIF2α protein expression was the most VHL-dependent. Indeed,supporting an important role for HIF2α in VHL-dependent enhancerremodeling, only HIF2α and HIF1β were significantly enriched atenhancers showing VHL-dependent H3K27ac depletion (FIG. 5F). Moreover,among all known motifs in the HOMER database, HIF2α was the mostenriched motif at VHL-responsive enhancers exhibiting H3K27ac depletion(P=1×10⁻¹¹). In contrast, HIF1α was not enriched at enhancers showingH3K27ac depletion (FIG. 5F). Despite sharing many binding sites withHIF2α, HIF1α predominantly localized to promoter-proximal regions,whereas HIF2α frequently occupied introns and intergenic regions in786-O cells (FIG. 5G), consistent with a promoter-centric occupancy ofHIF1a and an enhancer-centric occupancy of HIF2α (FIG. 5H). Gainedenhancers displayed a HIF2α occupancy twice that of tumour-specificpromoters (P<1×10⁻¹⁶, proportions test) in 786-O cells, suggesting thatHIF2α may play a greater role in regulating enhancers than promoters.

To extend these HIF1α and HIF2α occupancy-pattern findings to a systemthat expresses endogenous levels of both factors, HIF1α and HIF2αchromatin immunoprecipitation sequencing (ChIP-seq) was performed in40911432 clear cell renal cell carcinoma cells, which abundantlycoexpress both HIFα subunits (FIG. 5B). Similar to 786-O, in 40911432cells, HIF1α showed a preferential occupancy at promoter-proximalregions, whereas a large proportion of HIF2α was found in distal regions(introns and distal intergenic regions; FIG. 5I). A higher proportion ofHIF1α binding sites overlapped with gained promoters than HIF2α (68% ofHIF1α vs. 41% of HIF2α, P=0.002, proportions test; FIG. 5J). Conversely,a higher proportion of HIF2α binding sites overlapped with gainedenhancers than HIF1α (29% of HIF1α vs. 51% of HIF2α, P<2.2×10⁻¹⁶,proportions test). HIF2α's preferential occupancy at enhancers wasfurther substantiated by its higher enrichment at enhancers showingH3K27ac depletion after von Hippel-Lindau (VHL) restoration than HIF1α(FIG. 5K). Specific examples of VHL-responsive enhancers boundexclusively by HIF2α but not HIF1α included an enhancer near UBR4 (FIG.5L) and a superenhancer near CM/P (FIG. 5M). Therefore, even inHIF1α/HIF2α coexpressing clear cell renal cell carcinoma cells, theseresults suggest that HIF2α plays a greater role in VHL-mediated enhancerremodeling than HIF1α.

Example 7—HIF2α-HIF1β Bound Enhancers Modulate Gene Expression

To investigate the extent to which HIF2α silencing is sufficient torecapitulate the effects of von Hippel-Lindau (VHL) restoration, H3K27acchromatin immunoprecipitation sequencing (ChIP-seq) and RNA sequencing(RNA-seq) was performed in 786-O cells with HIF2α siRNA-mediatedknockdown and analyzed correlations between HIF2α siRNA knockdown andVHL restoration. When assessed against all genes, there was a lowcorrelation (r=0.1, P=5.2×10⁻³¹) between HIF2α knockdown and VHLrestoration. Importantly, however, this correlation increased to 0.23(P=5.8×10⁻¹⁴) for genes near HIF2α binding sites (FIG. 6A). Similarresults were obtained at the epigenomic level, where for gainedenhancers the correlation was low at 0.06 across all gained enhancers(P=1.9×10⁻⁵) but increased substantially to 0.37 (P=9.5×10⁻⁸) atHIF2α-bound enhancers (FIG. 6B) and at super-enhancers increased from0.089 (P=0.0025) to 0.25 (P=0.00054) at HIF2α-bound super-enhancers(FIG. 6C). As a visual example, H3K27ac signals at the ZNF395super-enhancer were diminished after VHL restoration or HIF2α knockdown,concomitant with decreased ZNF395 gene expression (FIG. 6D). Validationby RT-qPCR showed that HIF2α siRNA knockdown downregulated VEGFA,SLC2A1, and ZNF395 expression to a comparable degree as VHL restoration(FIG. 6E). Decreases in luciferase reporter activity of enhancerelements were also consistent between HIF2α siRNA knockdown and VHLrestoration (FIG. 6F).

It was aimed to establish a causal link between HIF2α-bound enhancersand control of gene expression. CRISPR-mediated genomic depletion of theZNF395 enhancer region with the highest HIF2α peak was performed (FIG.6G). All four clones with the homozygous deleted ZNF395 enhancerconsistently downregulated their ZNF395 expression compared with cloneswith the intact enhancer (P<0.05), providing evidence that ZNF395expression is epigenetically controlled by this HIF2α—HIF1β-boundenhancer (FIG. 6G). Taken together, these results indicate that thatHIF2α is an important mediator of von Hippel-Lindau (VHL)-drivenenhancer remodeling.

Example 8—Von Hippel-Lindau (VHL) Restoration Reduced P300 Recruitmentbut Preserved Promoter-Enhancer Interactions

Finally, this study sought to investigate the reason von Hippel-Lindau(VHL) restoration caused a decrease in H3K27ac levels. Previous pulldownassays have reported that both HIF2α and HIF1β can interact with histoneacetyltransferase p300. Indeed, p300 frequently marks enhancers and isthought to be recruited by tissue-specific transcription factors.However, chromatin profiles of p300 have not been previously establishedin kidney cancer cell lines, so the contribution of p300 in shapingenhancers in clear cell renal cell carcinoma remains unclear. Therefore,p300 chromatin immunoprecipitation sequencing (ChIP-seq) was performedin 786-O cells and confirmed its enrichment at gained enhancers overlost enhancers (FIG. 7A). Comparing p300 ChIP-seq with HIF2α ChIP-seqyielded a surprisingly high degree of overlap between HIF2α and p300(96%), even more than that of HIF2α and HIF1β (89%; FIGS. 7B and 7C). Incontrast, other transcription factors such as c-Jun, ETS1, and NF-κB didnot exhibit such a high degree of overlap (60%; FIG. 7B).

p300 binding at tumour enhancers with and without VHL was compared.Despite increased p300 protein levels in 786-O cells after VHLrestoration (FIG. 7D), binding of p300 decreased across all threeenhancers examined (FIG. 7E). HIF2α depletion by siRNA knockdown alsodecreased p300 recruitment (FIG. 7F), suggesting that loss of HIF2α mayinterfere with p300 recruitment.

It was investigated whether von Hippel-Lindau (VHL) restoration and thesubsequent loss of p300 binding disrupted promoter-enhancerinteractions. Capture-C of enhancer regions in paired 786-O cell lineswith and without VHL restoration was performed. Capture-C interactionsshowed a relatively high correlation between VHL-deficient andVHL-restored 786-0 cells at VHL-responsive regions (r=0.74, Pearsoncorrelation), even higher than correlations observed atnon-VHL-responsive regions (r=0.57, Pearson correlation; FIG. 7G). As avisual example, interactions between the VEGFA promoter and enhancerwere intact even after VHL restoration (FIG. 7H), indicating that lossof enhancer activity is likely insufficient to dissociatepromoter-enhancer interactions. Furthermore, many of thesepromoter-enhancers were lineage specific; for example, the interactionbetween SLC2A1 enhancer with its promoter was not detected in KATOIII, agastric cancer cell line (FIG. 7J). Therefore, promoter-enhancerinteractions often preexist in kidney cells, frequently in atissue-specific manner.

Clear cell renal cell carcinoma biomarkers were analysed from exosomesobtained from the culture medium of clear cell renal cell carcinoma cellline (A498) and normal kidney cell line (HK2), by measuring geneexpression of the biomarkers by quantitative polymerase chain reaction(qPCR) (FIG. 8 ). ERGIC, EGLN3, ETS1, PVT1, MYC, SMPDL3A, SNX10, VEGFAand ZNF395 (FIGS. 8A, 8B and 8C) showed higher expression in clear cellrenal cell carcinoma cell line compared to normal kidney cell line.

Microarray data from patient cohorts with clear cell renal cellcarcinoma or benign oncocytoma were compared. Expression levels ofVEGFA. EGLN3, ZNF395, SLC6A3 and SLC28A1 are higher in clear cell renalcell carcinoma compared to benign oncocytoma as shown by higher Z scorevalues (FIG. 9 ).

TABLE 5 A list of genes and proteins, and their accession numbers.Accession number Sequence ZNF395 NM_018660.2aagtgcgcat gtgcgcgagg agtcgctcgg gcacttattg agcgccgact mRNAgtctacgggcggccgggggt gatgggcaga ggcttcagtg tccccttcgc (SEQ IDctccgcagga gaggagaggcagcagcatgg cgagtgtcct gtcccgacgc NO: 43)cttggaaagc ggtccctcct gggagcccgggtgttgggac ccagtgcctcggaggggccc tcggctgccc caccctcgga gccactgcta gaaggggccgctccccagcc tttcaccacc tctgatgaca ccccctgcca ggagcagcccaaggaagtcc ttaaggctcc cagcacctcg ggccttcagc aggtggcctttcagcctggg cagaaggttt atgtgtggta cgggggtcaa gagtgcacaggactggtgga gcagcacagctggatggagg gtcaggtgac cgtctggctgctggagcaga agctgcaggt ctgctgcagggtggaggagg tgtggctggcagagctgcag ggcccctgtc cccaggcacc acccctggagcccggagcccaggccctggc ctacaggccc gtctccagga acatcgatgt cccaaagaggaagtcggacg cagtggaaat ggatgagatg atggcggcca tggtgctgacgtccctgtcctgcagccctg ttgtacagag tcctcccggg accgaggccaacttctctgc ttcccgtgcggcctgcgacc catggaagga gagtggtgacatctcggaca gcggcagcag cactaccagcggtcactgga gtgggagcagtggtgtctcc accccctcgc ccccccaccc ccaggccagccccaagtatttgggggatgc ttttggttct ccccaaactg atcatggctt tgagaccgatcctgaccctt tcctgctgga cgaaccagct ccacgaaaaa gaaagaactctgtgaaggtgatgtacaagt gcctgtggcc aaactgtggc aaagttctgcgctccattgt gggcatcaaa cgacacgtca aagccctcca tctgggggacacagtggact ctgatcagtt caagcgggag gaggatttct actacacagaggtgcagctg aaggaggaat ctgctgctgc tgctgctgctgctgccgcaggcaccccagt ccctgggact cccacctccg agccagctcc cacccccagcatgactggcc tgcctctgtc tgctcttcca ccacctctgc acaaagcccagtcctccggc ccagaacatc ctggcccgga gtcctccctg ccctcaggggctctcagcaa gtcagctcctgggtccttct ggcacattca ggcagatcatgcataccagg ctctgccatc cttccagatc ccagtctcac cacacatctacaccagtgtc agctgggctg ctgccccctc cgccgcctgc tctctctctccggtccggag ccggtcgcta agcttcagcg agccccagca gccagcacctgcgatgaaat ctcatctgat cgtcacttct ccaccccggg cccagagtggtgccaggaaa gcccgagggg aggctaagaa gtgccgcaag gtgtatggcatcgagcaccg ggaccagtgg tgcacggcct gccggtggaa gaaggcctgccagcgctttc tggactgagc tgtgctgcag gttctactct gttcctggccctgccggcag ccactgacaa gaggccagtg tgtcaccagc cctcagcagaaaccgaaaga gaaagaacgg aaacacggag tttgggctct gttggctaaggtgtaacacttaaagcaattttctcccattgtgcgaacattttattttttaaaaaaaaga aacaaaaata tttttccccc taaaataggagagagccaaaactgaccaag gctattcagc agtgaaccag tgaccaaaga attaattaccctccgtttcc cacatcccca ctctctaggg gattagcttg tgcgtgtcaaaagaaggaac agctcgttct gcttcctgct gagtcggtga attctttgctttctaaactc ttccagaaag gactgtgagc aagatgaatt tacttttcttaaaaaaaaaa aaaaaaaaaa aaaaaaagag tttctggctg atgggtgactcagagtgcaggactgcctgg ccgtggggca gaggggtttg cccttctcggagggtacctc ctgttccctg tctgagcatc ctgcatggaa gtcaaaggaaatccctttct tggtgacgac ttaaatctgg gttccctcag acattgggttgcaccccaac aaatattaaa tggcttcttc ttaaagccca gagaaagaggttttttaaaa gactgtcgcc aaatagctga gccaaaaggc tgatcagaattcactttttg gaatgtggca gttaaacact accttgatca ttctctcctctttcctcgaggaactcctgg agggtttgag cgtctggaaa ctctctgctctgacccgagg aagcaccctc ctgacgccgc cttcctccgg ttattgaaaggacgcctcag aaatgctttg ttttctttta cgatgtattc agaagcctttactgattaaa gttttctttt atttgggtgg ccgggagaga cccagggaggttctggaggt tcctttctgt ctcctggccc caccagggat ttccccatttctgtttgctg cctgaaagca ggatgaggaa ggccaaggag agtccttgcacccgtgagcg tcaggatgag gaaatgacag gaggaagacg tgggtttgggttagtggctg ctggcgttttggcccttggt gtttctggag cctccagggatctaggggag cctgggctgc gtgcatgtcg ataagcagag ctgttcttggggagaaggag ggaggtctcg ggagtgtagc accatgccaa ccagccctgcgcgaagacag agtgagccac gcccggatgg cagggcatgt ttctgttttggtgtctcact ttcctcccag cgtgacttat ttggggattc ctcagggcctactggaatgt gactgcccac tgcccagctg cctcgggtac aagtcctggccctatgtccc agctgtcaggggctcaggga atcctaccca gccacctgtcctgggatgga gtgtcagcat ccaccccttg gttgtcatcg aggccgccctcccagtcctg ggtgaagata tttgggccac cagggctccc ttggccccttcacgtaggaa atagacacgt gctttttaat gcaggacact ttgagtgttacaaaatctgt agacctggca gtagggtcat gatgttggga agggtgtagtgccctaggtt ggtgacagaa gggacagaca cttgtgcaca ggtgtctttggtgatggggt tttttttttt ataacttagt aaaaaaaaaa aaatgtatgtggaattctgt ctcttggtaa agctcaaagc caggctagcc tgaggtggcgcagggctctc cttcctgtcc cttcgatctc cttgagaatt aagagctggcagctgctgat ggtgtttccc aacccccctc acttcccaag acaacccccagcttcaggtc ctcatgggga ggggagggca cgttcttgac acatgggaacttcgctcagg agggcctccc cttcccctct ccctcagagt tttcactgccgtctcgtctt tagaaagctg tttgaattcc ccccgccccc agtttggaccgtgtagatat aactggatat acggattttt ctctttgtgc aggcttcttatgccgttggt atacagggca ggaaagagag gaataaaggg agagagcagtgtggaaacca cggtggtttt gctttgttct tactaggttt tggtgccaccttccctgcct gcgcttgtgc cccctctcct ccttggcact ggcggcctccttgcctccct tccacccgtg ctgccatccc gtgcctgtcg tgttggttcttcacacgtgc tctgttctcg gggttgttcc attcatgcct tcttggagggtgagggtggc ttgggaaccg acccagtgat catgcctact ttcttctttgtatctccctc cttcccagcc cacccgggca gcagactctg atggaaggaaggtgccgtag gtgggctttt agaaactaac gggactggtt ttcaaagcagttatcttggg aaactgttta ttccagcgat gtgacttttt tcagaatatttcttggaatc atattcagag tctggggctg tgtgttgagc agccttaaggatgctagaca ctcatttagtgcccagggag tccagcgaat gacgtctgtggccaagcgag gtctcaggtg caaagcaaaa ggaccattta aagtaaaatagcttggattc aatcatgtga cttttaaatt ggctcagaaa gcaattttgtaatttcagag agtgttttga gccatggcca cgttgtcatt gtgagtctatagcttgactc cttggagaac aatattcatt tggttgtgga gactgatttgctgggagaaa tctgtcctgt tactttctgg tcatcccagg ttctgacttttaccaggggc aaaaaaaaaaaaagcaagag ggagataaat cccatctgtgagtttgtctt attggcgcct ttttcctcag ctgtcttcca agtattatttttactgttaa aaaatttttt aaaaatgtga aatgtaatgt ttttacagcaacaatatgaa atatatttta taaggaataa aatggtacct tgtctgattt aaaaaaa ZNF395NP_061130.1 masvlsrrlg krsllgarvl gpsasegpsa appseplleg aapqpfttsdprotein dtpcqeqpkevlkapstsgl qqvafqpgqk vyvwyggqec tglveqhswm (SEQ IDegqvtvwlle qklqvccrveevwlaelqgp cpqapplepg aqalayrpvs NO: 44)rnidvpkrks davemdemma amvltslscspvvqsppgte anfsasraacdpwkesgdis dsgssttsgh wsgssgvstp spphpqaspkylgdafgspqtdhgfetdpd pflldepapr krknsvkvmy kelwpncgkvIrsivgikrhvkalhlgdtv dsdqfkreed fyytevqlke esaaaaaaaaagtpvpgtpt sepaptpsmtglplsalppp Ihkaqssgpe hpgpesslpsgalsksapgs fwhiqadhay qalpsfqipvsphiytsvsw aaapsaacslspvrsrslsf sepqqpapam kshlivtspp raqsgarkargeakkerkvygiehrdqwet acrwkkacqr fld SMPDL3A NM_001286138.1accagtatgt cagtgtttga catcaactgc accactgata cacgagtcgg mRNAaatttgagcttctacaagta cattccttcc taggccaaac actgacgcta agaaatacga(isoform b)gaacagatcatcgctaaaca gcagctgaag gtcaggcgaa ctgactcgct gcggaatctg (SEQ IDcctttgcacgtgatcagtcg gacgtctaca cccgcagccg tcttctgtct ccgcctcacc NO: 45)ctcaggcctgacggtccgag tggagctgcg ggacagcccg aacctccagg tcagccccgcggccctccatggcgctggtg cgcgcactcg tctgctgcct gctgactgcc tggcactgccgctccggcctcgggctgccc gtggcgcccg caggcggcag gaatcctcct ccggcgatagggatagcccacctcatgttc ctgtacctga actctcaaca gacactgtta taaatgtgatcactaatatgacaaccacca Tccagagtct Ctttccaaat ctccaggttt tccctgcgctgggtaatcatgactattggc cacaggatca actgcctgta gtcaccagta aagtgtacaatgcagtagcaaacctctgga aaccatggct agatgaagaa gctattagta ctttaaggaaaggtggtttttattcacaga aagttacaac taatccaaac cttaggatca tcagtctaaacatagcacatgttccagtgg gagacagcat tatggttctt aacatcacag caatgagagaatactataatgagaaattga gactgtttca ggcgaatcta agtgatgtca ttgcaggacaattttatggacacactcaca atctgacaga atcttcacag tcagataaaa aaggaagtccagtaaattctttgtttgtgg ggtatctgcc tcaaaaatac aagagtgttt tagaaaaacagaccaacaatcctggtatca tagatatttt tacaccagtg cgtgattata aattattggatatgttgcagtattacttga ctcctgctgt gtatgatcct aagggagagt ccatctggaacacaaacttgtactacggcc caaatataat gacactgaac aagactgacc cagccaaccagtttgaatggctagaaagta cattgaacaa ctctcagcag aataaggaga aggtgtatatgctggagtatatcctgaccc agacctacga cattgaagat ttgcagccgg aaagtttatatggattagctaaacaattta caatcctaga cagtaagcag tttataaaat actacaattacttctttgtgagttatgaca gcagtgtaac atgtgataag acatgtaagg cctttcagatttgtgcaattatgaatcttg ataatatttc ctatgcagat tgcctcaaac agctttatataaagcacaattactagtatt tcacagtttt tgctaataga aaatgctgat tctgattctgagatcaatttgtgggaattt tacataaatc tttgttaatt actgagtggg caagtagactgggtaatcatgactattggc cacaggatca actgcctgta gtcaccagta aagtgtacaacacaaacttgtactacggcc caaatataat gacactgaac aagactgacc cagccaaccagtttgaatggctagaaagta cattgaacaa ctctcagcag aataaggaga aggtgtatatttgcagccgg aaagtttata SMPDL3A NP_001273067.1mtttiqslfp nlqvfpalgn hdywpqdqlp vvtskvynav anlwkpwlde proteineaistlrkggfysqkvttnp nlriislntn lyygpnimtl nktdpanqfe wlestInnsq(isoform b)qnkekvyiiahvpvgylpss qnitamreyy neklidifqk ysdviagqfy ghthrdsimv (SEQ IDIsdkkgspvnslfvapavtp vksvlekqtn npgirlfqyd prdyklldml qyylnltean NO: 46)Ikgesiwkleyiltqtydie dlqpeslygl akqftildsk qfikyynyff vsydssvtcdktckafqicaimnldnisya delkqlyikh ny SMPDL3A NM_006714.4accagtatgt cagtgtttga catcaactgc accactgata cacgagtcgg proteinaatttgagcttctacaagta cattccttcc taggccaaac actgacgcta agaaatacga(isoform a)gaacagatcatcgctaaaca gcagctgaag gtcaggcgaa ctgactcgct gcggaatctg (SEQ IDcctttgcacgtgatcagtcg gacgtctaca cccgcagccg tcttctgtct ccgcctcacc NO: 47)ctcaggcctgacggtccgag tggagctgcg ggacagcccg aacctccagg tcagccccgcggccctccatggcgctggtg cgcgcactcg tctgctgcct gctgactgcc tggcactgccgctccggcctcgggctgccc gtggcgcccg caggcggcag gaatcctcct ccggcgataggacagttttggcatgtgact gacttacact tagaccctac ttaccacatc acagatgaccacacaaaagtgtgtgcttca tctaaaggtg caaatgcctc caaccctggc ccttttggagatgttctgtgtgattctccatatcaacttattttgtcagcatttgattttattaaaaattctggacaagaagcat ctttc atgatatgga caggggatag cccacctcat gttcctgtacctgaactctcaacagacact gttataaatgtgatcactaa tatgacaacc accatccaga gtctctttccaaatctccag gttttccctgcgctgggtaa tcatgactat tggccacagg atcaactgcctgtagtcacc agtaaagtgtacaatgcagt agcaaacctc tggaaaccat ggctagatgaagaagctatt agtactttaaggaaaggtgg tttttattca cagaaagtta caactaatccaaaccttagg atcatcagtctaaacacaaa cttgtactac ggcccaaata taatgacactgaacaagact gacccagccaaccagtttga atggctagaa agtacattga acaactctcagcagaataag gagaaggtgtatatcatagc acatgttcca gtggggtatc tgccatcttcacagaacatc acagcaatgagagaatacta taatgagaaa ttgatagata tttttcaaaaatacagtgat gtcattgcag gacaattttatggacacact cacagagaca gcattatggttctttcagat aaaaaaggaa gtccagtaaattctttgttt gtggctcctg ctgttacaccagtgaagagt gttttagaaa aacagaccaa caatcctggtatcagactgt ttcagtatgatcctcgtgat tataaattat tggatatgtt gcagtattac ttgaatctgacagaggcgaatctaaaggga gagtccatct ggaagctgga gtatatcctg acccagacctacgacattgaagatttgcag ccggaaagtt tatatggatt agctaaacaa tttacaatcctagacagtaagcagtttata aaatactaca attacttctttgtgagttatgacagcagtgtaacatgtgataagacatgtaaggcctttcagatttgtgcaattatgaatcttgataatatttcctatgcagattgcctcaaacagctttatataaagcacaattactagtatttcacagtttttgctaatagaaaatgctgattctgattctgagatcaatttgtggga attttacataaatctttgttaattactgagtgggcaagtagacttcctgtctttgctttctttttttttttctttttgatgccttaatgtagatatctttatcattctgaattgtattatatatttaaagtgctcattaatagaatgatggatgtaaatt ggatgtaaat attcagtttatataattatatctaatttgtacccttgttg aaattgtcat ttatacaata aagcgaattc tttatctctaaaaaaaaaaaaaaaaaa SMPDL3A NP_006705.1malvralvcc lltawhersg lglpvapagg rnpppaigqf whvtdlhldp tyhitddhtkproteinvcasskgana snpgpfgdvl cdspyqlils afdfiknsgq easfmiwtgd spphvpvpel(isoform a)stdtvinvit nmtttiqslf pnlqvfpalg nhdywpqdql pvvtskvyna vanlwkpwld(SEQ IDeeaistlrkg gfysqkvttn pnlriislnt nlyygpnimt Inktdpanqf ewlestlnnsNO: 48)qqnkekvyii ahvpvgylps sqnitamrey yneklidifq kysdviagqf yghthrdsimvlsdkkgspv nslfvapavt pvksvlekqt nnpgirlfqy dprdyklldm lqyylnlteanlkgesiwkl eyiltqtydi edlqpeslyg lakqftilds kqfikyynyf fvsydssvtcdktckafqic aimnldnisy adclkqlyik hny SLC28A1 NM_001287761.1acaacgatgt gaaggttata agctgcactg catggttgctgctggatgtgttgtgttcctggcttccctcmRNA tggatgctga cagaaacaag gctggaaggt ctgggacatg gagaacgacc (SEQ IDcctcgagacg aagagagtcc atctctctca cacctgtggc caagggtctg gagaacatggNO: 49)gggctgattt cttggaaagc ctggaggaag gccagctccc taggagtgac ttgagccccgcagagatcag gagcagctgg agcgaggcgg cgccgaagcc cttctccaga tggaggaacctgcagccagc cctgagagcc agaagcttct gcagggagca catgcagctg tttcgatggatcggcacagg cctgctctgc actgggctct ctgccttcct gctggtggcc tgcctcctggatttccagag ggccctggct ctgtttgtcc tcacctgtgt ggtcctcacc ttcctgggccaccgcctgct gaaacggctt ctggggccaa agctgaggag gtttctcaag cctcagggccatccccgcct gctgctctgg tttaagaggg gtctagctct tgctgctttc ctgggcctggtcctgtggct gtctctggac acctcccagc ggcctgagca actggtgtcc ttcgcaggaatctgcgtgtt cgtcgctctc ctctttgcct gctcaaagca tcattgcgca gtgtcctggagggccgtgtc ttggggactt ggactgcagt ttgtacttgg actcctcgtc atcagaacagaaccaggatt cattgcgttc gagtggctgg gcgagcagat ccggatcttc ctgagctacacgaaggctgg ctccagcttc gtgtttgggg aggcgctggt caaggatgtc tttgcctttcaggttctgcc catcattgtc tttttcagct gtgtcatatc cgttctctac cacgtgggcctcatgcagtg ggtgatcctg aagattgcct ggctgatgca agtcaccatg ggcaccacagccactgagac cctgagtgtg gctggaaaca tctttgtgag ccagaccgag gctccattactgatccggcc ctacttggca gacatgacac tctctgaagt ccacgttgtc atgaccggaggttacgccac cattgctggc agcctgctgg gtgcctacat ctcctttggg gtcagagctgaagtcctcac gacgtttgcc ctctgtggat ttgccaattt cagctccatt gggatcatgctgggaggctt gacctccatg gtcccccaac ggaagagcga cttctcccag atagtgctccgggcgctctt cacgggagcc tgtgtgtccc tggtgaacgc ctgtatggca gggatcctctacatgcccag gggggctgaa gttgactgca tgtccctctt gaacacgacc ctcagcagcagtagctttga gatttaccag tgctgccgtg aggccttcca gagcgtcaat ccagagttcagcccagaggc cctggacaac tgctgtcggt tttacaacca cacgatctgt gcacagtgaggacagaacat gcttgtgctt ctgcgcttct gagggctgtt ctcccccggg aaccatctgtccccaccttc cctttcccag agccctcttc agggaagcca caggacttag acccagctcaatcccacaat tgggaagggt tcatggagtg agtgtgcaga gagtgagtga ggacataaggaaggacatgt cccactccat cccccttcct gctcccccat ttcctaactc ccccagtgtgaattctcagg gtcacttctg cctcctcccg tttcccctcc acatccaaac agcaccctggtcctctctat cccccctctc ctggggtccc tcacatgccc cttcccttct gttgtgggctgcacaccaaa gcctcctccc ctccccactt cctaggcact aggatctctc tgtggcttcccctgctgggt ggtgtcacct ctttctctgc tttcagagaa acccttcccg cctttcctcagagtgcttcc caaactgagg tcccatggca cactgtcctg ggaggcgttc agagggttccatgatggact aggtttggaa ccactgggtt aaataaactt agagagggct gttta SLC28A1NP_001274690.1mendpsrrre sisltpvakg lenmgadfle sleegqlprs dlspaeirss wseaapkpfsproteinrwrnlqpalr arsfcrehmq lfrwigtgll ctglsafllv aclldfqral alfvltcvvl(SEQ IDtflghrllkr llgpklrrfl kpqghprlll wfkrglalaa flglvlwlsl dtsqrpeqlvNO: 50)sfagicvfva llfacskhhc avswravswg lglqfvlgll virtepgfia fewlgeqiriflsytkagss fvfgealvkd vfafqvlpii vffscvisvl yhvglmqwvi lkiawlmqvtmgttatetls vagnifvsqt eapllirpyl admtlsevhv vmtggyatia gsllgayisfgvraevlttf alcgfanfss igimlgglts mvpqrksdfs qivlralftg acvslvnacmagilymprga evdcmsllnt tlssssfeiy qccreafqsv npefspeald nccrfynhti caqVEGFA NM_001025366.2tcgcggaggc ttggggcagc cgggtagctc ggaggtcgtg gcgctggggg ctagcaccag mRNAcgctctgtcg ggaggcgcag cggttaggtg gaccggtcag cggactcacc ggccagggcg(SEQ IDctcggtgctg gaatttgata ttcattgatc cgggttttat ccctcttctt ttttcttaaaNO: 51)catttttttt taaaactgta ttgtttctcg ttttaattta tttttgcttg ccattccccacttgaatcgg gccgacggct tggggagatt gctctacttc cccaaatcac tgtggattttggaaaccagc agaaagagga aagaggtagc aagagctcca gagagaagtc gaggaagagagagacggggt cagagagagc gcgcgggcgt gcgagcagcg aaagcgacaggggcaaagtgagtgacctgc ttttgggggt gaccgccgga gcgcggcgtg agccctcccccttgggatcccgcagctgac cagtcgcgct gacggacaga cagacagaca ccgcccccagccccagctaccacctcctcc ccggccggcg gcggacagtg gacgcggcgg cgagccgcgggcaggggccggagcccgcgc ccggaggcgg ggtggagggg gtcggggctc gcggcgtcgcactgaaacttttcgtccaac ttctgggctg ttctcgcttc ggaggagccg tggtccgcgcgggggaagccgagccgagcg gagccgcgag aagtgctagc tcgggccggg aggagccgcagccggaggagggggaggagg aagaagagaa ggaagaggag agggggccgc agtggcgactcggcgctcggaagccgggct catggacggg tgaggcggcg gtgtgcgcag acagtgctccagccgcgcgcgctccccagg ccctggcccg ggcctcgggc cggggaggaa gagtagctcgccgaggcgccgaggagagcg ggccgcccca cagcccgagc cggagaggga gcgcgagccgcgccggccccggtcgggcct ccgaaaccat gaactttctg ctgtcttggg tgcattggagccttgccttgctgctctacc tccaccatgc caagtggtcc caggctgcac ccatggcagaaggaggagggcagaatcatc acgaagtggt gaagttcatg gatgtctatc agcgcagctactgccatccaatcgagaccc tggtggacat cttccaggag taccctgatg agatcgagtacatcttcaagccatcctgtg tgcccctgat gcgatgcggg ggctgctgca atgacgagggcctggagtgtgtgcccactg aggagtccaa catcaccatg cagattatgc ggatcaaacctcaccaaggccagcacatag gagagatgag cttcctacag cacaacaaat gtgaatgcagaccaaagaaa gatagagcaa gacaagaaaa aaaatcagtt cgaggaaagg gaaaggggcaaaaacgaaagcgcaagaaat cccggtataa gtcctggagc gtgtacgttg gtgcccgctgctgtctaatgccctggagcc tccctggccc ccatccctgt gggccttgct cagagcggagaaagcattttttgtacaag atccgcagac gtgtaaatgt tcctgcaaaa acacagactcgcgttgcaaggcgaggcagc ttgagttaaa cgaacgtact tgcagatgtg acaagccgaggcggtgagccgggcaggagg aaggagcctc cctcagggtt tcgggaacca gatctctcaccaggaaagactgatacagaa cgatcgatac agaaaccacg ctgccgccac cacaccatcaccatcgacagaacagtcctt aatccagaaa cctgaaatga aggaagagga gactctgcgcagagcactttgggtccggag ggcgagactc cggcggaagc attcccgggc gggtgacccagcacggtccctcttggaatt ggattcgcca ttttattttt cttgctgcta aatcaccgagcccggaagattagagagttt tatttctggg attcctgtag acacacccac ccacatacatacatttatatatatatatat tatatatata taaaaataaa tatctctatt ttatatatataaaatatatatattcttttt ttaaattaac agtgctaatg ttattggtgt cttcactggatgtatttgac tgctgtggac ttgagttggg aggggaatgt tcccactcag atcctgacagggaagaggaggagatgagag actctggcat gatctttttt ttgtcccact tggtggggccagggtcctctcccctgccca ggaatgtgca aggccagggc atgggggcaa atatgacccagttttgggaacaccgacaaa cccagccctg gcgctgagcc tctctacccc aggtcagacggacagaaagacagatcacag gtacagggat gaggacaccg gctctgacca ggagtttggggagcttcaggacattgctgt gctttgggga ttccctccac atgctgcacg cgcatctcgcccccaggggcactgcctgga agattcagga gcctgggcgg ccttcgctta ctctcacctgcttctgagttgcccaggaga ccactggcag atgtcccggc gaagagaaga gacacattgttggaagaagcagcccatgac agctcccctt cctgggactc gccctcatcc tcttcctgctccccttcctggggtgcagcc taaaaggacc tatgtcctca caccattgaa accactagttctgtccccccaggagacctg gttgtgtgtg tgtgagtggt tgaccttcct ccatcccctggtccttcccttcccttcccg aggcacagag agacagggca ggatccacgt gcccattgtggaggcagagaaaagagaaag tgttttatat acggtactta tttaatatcc ctttttaatt agaaattaaaacagttaatt taattaaaga gtagggtttt ttttcagtat tcttggttaa tatttaatttcaactatttatgagatgtat cttttgctct ctcttgctct cttatttgta ccggtttttgtatataaaat tcatgtttccaatctctctc tccctgatcg gtgacagtca ctagcttatcttgaacagat atttaatttt gctaacactcagctctgccc tccccgatcc cctggctccccagcacacat tcctttgaaa taaggtttcaatatacatct acatactata tatatatttggcaacttgta tttgtgtgta tatatatata tatatgtttatgtatatatg tgattctgataaaatagaca ttgctattct gttttttata tgtaaaaaca aaacaagaaaaaatagagaattctacatac taaatctctc tcctttttta attttaatat ttgttatcatttatttattggtgctactgt ttatccgtaa taattgtggg gaaaagatat taacatcacgtctttgtctctagtgcagtt tttcgagata ttccgtagta catatttatt tttaaacaacgacaaagaaatacagatata tcttaaaaaa aaaaaagcat tttgtattaa agaatttaattctgatctcaaaaaaaaaaa aaaaaaa VEGFA NP_001020537.2mtdrqtdtap spsyhllpgr rrtvdaaasr gqgpepapgg gvegvgargv alklfvqllgproteincsrfggavvr ageaepsgaa rsassgreep qpeegeeeee keeergpqwr lgarkpgswt(SEQ IDgeaavcadsa paarapqala rasgrggrva rrgacesgpp hspsrrgsas ragpgrasetNO: 52) mnfllswvhw slalllylhh akwsqaapma egggqnhhev vkfmdvyqrsychpietlvdifqeypdeie yifkpscvpl mreggcende glecvptees nitmqimrikphqgqhigemsflqhnkcec rpkkdrarqe kksvrgkgkg qkrkrkksry kswsvyvgarcclmpwslpgphpcgpcser rkhlfvqdpq tckcsckntd srckarqlel nertcredkp rrEGLN3 NM_001308103.1ggcttcgcgc tcgtgtagat cgttccctct ctggttgcac gctggggatc ccggacctcg mRNAattctgcggg cgagatgccc ctgggacaca tcatgaggct ggacctggag aaaattgccc(isoform 1)tggagtacat cgtgccctgt ctgcacgagg caatggtggc ttgctatccg ggaaatggaa(SEQ IDcaggttatgt tcgccacgtg gacaacccca acggtgatgg tcgctgcatc acctgcatctNO: 53)actatctgaa caagaattgg gatgccaagc tacatggtgg gatcctgcgg atatttccagaggggaaatc attcatagca gatgtggagc ccatttttga cagactcctg ttcttctggtcagatcgtag gaacccacac gaagtgcagc cctcttacgc aaccagatat gctatgactgtctggtactt tgatgctgaa gaaagggcag aagccaaaaa gaaattcagg aatttaactaggaaaactga atctgccctc actgaagact gaccgtgctc tgaaatctgc tggccttgttcattttagta acggttcctg aattctctta aattctttga gatccaaaga tggcctcttcagtgacaaca atctccctgc tacttcttgc atccttcaca tccctgtctt gtgtgtggtacttcatgttt tcttgccaag actgtgttga tcttcagata ctctctttgc cagatgaagttacttgctaa ctccagaaat tcctgcagac atcctactcg gccagcggtt tacctgatagattcggtaat actatcaaga gaagagccta ggagcacagc gagggaatga accttacttgcactttatgt atacttcctg atttgaaagg aggaggtttg aaaagaaaaa aatggaggtggtagatgcca cagagaggca tcacggaagc cttaacagca ggaaacagag aaatttgtgtcatctgaaca atttccagat gttcttaatc cagggctgtt ggggtttctg gagaattatcacaacctaat gacattaata cctctagaaa gggctgctgt catagtgaac aatttataagtgtcccatgg ggcagacact ccttttttcc cagtcctgca acctggattt tctgcctcagccccattttg ctgaaaataa tgactttctg aataaagatg gcaacacaat tttttctccattttcagttc ttacctggga acctaattcc ccagaagcta aaaaactaga cattagttgttttggttgct ttgttggaat ggaatttaaa tttaaatgaa aggaaaaata tatccctggtagttttgtgt taaccactga taactgtgga aagagctagg tctactgata tacaataaacatgtgtgcat cttgaacaat ttgagagggg aggtggagtt ggaaatgtgg gtgttcctgttttttttttt tttttttttt tagttttcct ttttaatgag ctcacccttt aacacaaaaaaagcaaggtg atgtatttta aaaaaggaag tggaaataaa aaaatctcaa agctatttgagttctcgtct gtccctagca gtctttcttc agctcacttg gctctctaga tccactgtggttggcagtat gaccagaatc atggaatttg ctagaactgt ggaagcttct actcctgcagtaagcacaga tcgcactgcc tcaataactt ggtattgagc acgtattttg caaaagctacttttcctagt tttcagtatt actttcatgt tttaaaaatc cctttaattt cttgcttgaaaatcccatga acattaaaga gccagaaata ttttcctttg ttatgtacgg atatatatatatatagtctt ccaagataga agtttacttt ttcctcttct ggttttggaa aatttccagataagacatgt caccattaat tctcaacgac tgctctattt tgttgtacgg taatagttatcaccttctaa attactatgt aatttattca cttattatgt ttattgtctt gtatcctttctctggagtgt aagcacaatg aagacaggaa ttttgtatat ttttaaccaa tgcaacatactctcagcacc taaaatagtg ccgggaacat agtaagggct cagtaaatac ttgttgaataaactcagtct cctacattag cattctaaaa aaaaaaaaa EGLN3 NP_001295032.1mplghimrld lekialeyiv pclheamvac ypgngtgyvr hvdnpngdgr citciyylnkproteinnwdaklhggi lrifpegksf iadvepifdr llffwsdrrn phevqpsyat ryamtvwyfd(isoform 1) aeeracakkk frnltrktes alted (SEQ ID NO: 54) EGLN3NM_022073.3gagtctggcc gcagtcgcgg cagtggtggc ttcccatccc caaaaggcgc cctccgactc mRNActtgcgccgc actgctcgcc gggccagtcc ggaaacgggt cgtggagctc cgcaccactc(isoform 2)ccgctggttc ccgaaggcag atcccttctc ccgagagttg cgagaaactt tcccttgtcc(SEQ IDccgacgctgc agcggctcgg gtaccgtggc agccgcaggt ttctgaaccc cgggccacgcNO: 55)tccccgcgcc tcggcttcgc gctcgtgtag atcgttccct ctctggttgc acgctggggatcccggacct cgattctgcg ggcgagatgc ccctgggaca catcatgagg ctggacctggagaaaattgc cctggagtac atcgtgccct gtctgcacga ggtgggcttc tgctacctggacaacttcct gggcgaggtg gtgggcgact gcgtcctgga gcgcgtcaag cagctgcactgcaccggggc cctgcgggac ggccagctgg cggggccgcg cgccggcgtc tccaagcgacacctgcgggg cgaccagatc acgtggatcg ggggcaacga ggagggctgc gaggccatcagcttcctcct gtccctcatc gacaggctgg tcctctactg cgggagccgg ctgggcaaatactacgtcaa ggagaggtct aaggcaatgg tggcttgcta tccgggaaat ggaacaggttatgttcgcca cgtggacaac cccaacggtg atggtcgctg catcacctgc atctactatctgaacaagaa ttgggatgcc aagctacatg gtgggatcct gcggatattt ccagaggggaaatcattcat agcagatgtg gagcccattt ttgacagact cctgttcttc tggtcagatcgtaggaaccc acacgaagtg cagccctctt acgcaaccag atatgctatg actgtctggtactttgatgc tgaagaaagg gcagaagcca aaaagaaatt caggaattta actaggaaaactgaatctgc cctcactgaa gactgaccgt gctctgaaat ctgctggcct tgttcattttagtaacggtt cctgaattct cttaaattct ttgagatcca aagatggcct cttcagtgacaacaatctcc ctgctacttc ttgcatcctt cacatccctg tcttgtgtgt ggtacttcatgttttcttgc caagactgtg ttgatcttca gatactctct ttgccagatg aagttacttgctaactccag aaattcctgc agacatccta ctcggccagc ggtttacctg atagattcggtaatactatc aagagaagag cctaggagca cagcgaggga atgaacctta cttgcactttatgtatactt cctgatttga aaggaggagg tttgaaaaga aaaaaatgga ggtggtagatgccacagaga ggcatcacgg aagccttaac agcaggaaac agagaaattt gtgtcatctgaacaatttcc agatgttctt aatccagggc tgttggggtt tctggagaat tatcacaacctaatgacatt aatacctcta gaaagggctg ctgtcatagt gaacaattta taagtgtcccatggggcaga cactcctttt ttcccagtcc tgcaacctgg attttctgcc tcagccccattttgctgaaa ataatgactt tctgaataaa gatggcaaca caattttttc tccattttcagttcttacct gggaacctaa ttccccagaa gctaaaaaac tagacattag ttgttttggttgctttgttg gaatggaatt taaatttaaa tgaaaggaaa aatatatccc tggtagttttgtgttaacca ctgataactg tggaaagagc taggtctact gatatacaat aaacatgtgtgcatcttgaa caatttgaga ggggaggtgg agttggaaat gtgggtgttc ctgttttttttttttttttt tttttagttt tcctttttaa tgagctcacc ctttaacaca aaaaaagcaaggtgatgtat tttaaaaaag gaagtggaaa taaaaaaatc tcaaagctat ttgagttctcgtctgtccct agcagtcttt cttcagctca cttggctctc tagatccact gtggttggcagtatgaccag aatcatggaa tttgctagaa ctgtggaagc ttctactcct gcagtaagcacagatcgcac tgcctcaata acttggtatt gagcacgtat tttgcaaaag ctacttttcctagttttcag tattactttc atgttttaaa aatcccttta atttcttgct tgaaaatcccatgaacatta aagagccaga aatattttcc tttgttatgt acggatatat atatatatagtcttccaaga tagaagttta ctttttcctc ttctggtttt ggaaaatttc cagataagacatgtcaccat taattctcaa cgactgctct attttgttgt acggtaatag ttatcaccttctaaattact atgtaattta ttcacttatt atgtttattg tcttgtatcc tttctctggagtgtaagcac aatgaagaca ggaattttgt atatttttaa ccaatgcaac atactctcagcacctaaaat agtgccggga acatagtaag ggctcagtaa atacttgttg aataaactcagtctcctaca ttagcattct aa EGLN3 NP_071356.1mplghimrld lekialeyiv pclhevgfcy ldnflgevvg dcvlervkql hctgalrdgqproteinlagpragvsk rhlrgdqitw iggneegcea isfllslidr lvlycgsrlg kyyvkerska(isoform 2)mvacypgngt gyvrhvdnpn gdgrcitciy ylnknwdakl hggilrifpe gksfiadvep(SEQ ID ifdrllffws drrnphevqp syatryamtv wyfdacerae akkkfrnltr ktesaltedNO: 56) SLC6A3 NM_001044.4cgctgcggag cgggagggga ggcttcgcgg aacgctctcg gcgccaggac tcgcgtgcaa mRNAagcccaggcc cgggcggcca gaccaagagg gaagaagcac agaattcctc aactcccagt(SEQ IDgtgcccatga gtaagagcaa atgctccgtg ggactcatgt cttccgtggt ggccccggctNO: 57)aaggagccca atgccgtggg cccgaaggag gtggagctca tccttgtcaa ggagcagaacggagtgcagc tcaccagctc caccctcacc aacccgcggc agagccccgt ggaggcccaggatcgggaga cctggggcaa gaagatcgac tttctcctgt ccgtcattgg ctttgctgtggacctggcca acgtctggcg gttcccctac ctgtgctaca aaaatggtgg cggtgccttcctggtcccct acctgctctt catggtcatt gctgggatgc cacttttcta catggagctggccctcggcc agttcaacag ggaaggggcc gctggtgtct ggaagatctg ccccatactgaaaggtgtgg gcttcacggt catcctcatc tcactgtatg tcggcttctt ctacaacgtcatcatcgcct gggcgctgca ctatctcttc tcctccttca ccacggagct cccctggatccactgcaaca actcctggaa cagccccaac tgctcggatg cccatcctgg tgactccagtggagacagct cgggcctcaa cgacactttt gggaccacac ctgctgccga gtactttgaacgtggcgtgc tgcacctcca ccagagccat ggcatcgacg acctggggcc tccgcggtggcagctcacag cctgcctggt gctggtcatc gtgctgctct acttcagcct ctggaagggcgtgaagacct cagggaaggt ggtatggatc acagccacca tgccatacgt ggtcctcactgccctgctcc tgcgtggggt caccctccct ggagccatag acggcatcag agcatacctgagcgttgact tctaccggct ctgcgaggcg tctgtttgga ttgacgcggc cacccaggtgtgcttctccc tgggcgtggg gttcggggtg ctgatcgcct tctccagcta caacaagttcaccaacaact gctacaggga cgcgattgtc accacctcca tcaactccct gacgagcttctcctccggct tcgtcgtctt ctccttcctg gggtacatgg cacagaagca cagtgtgcccatcggggacg tggccaagga cgggccaggg ctgatcttca tcatctaccc ggaagccatcgccacgctcc ctctgtcctc agcctgggcc gtggtcttct tcatcatgct gctcaccctgggtatcgaca gcgccatggg tggtatggag tcagtgatca ccgggctcat cgatgagttccagctgctgc acagacaccg tgagctcttc acgctcttca tcgtcctggc gaccttcctcctgtccctgt tctgcgtcac caacggtggc atctacgtct tcacgctcct ggaccattttgcagccggca cgtccatcct ctttggagtg ctcatcgaag ccatcggagt ggcctggttctatggtgttg ggcagttcag cgacgacatc cagcagatga ccgggcagcg gcccagcctgtactggcggc tgtgctggaa gctggtcagc ccctgctttc tcctgttcgt ggtcgtggtcagcattgtga ccttcagacc cccccactac ggagcctaca tcttccccga ctgggccaacgcgctgggct gggtcatcgc cacatcctcc atggccatgg tgcccatcta tgcggcctacaagttctgca gcctgcctgg gtcctttcga gagaaactgg cctacgccat tgcacccgagaaggaccgtg agctggtgga cagaggggag gtgcgccagt tcacgctccg ccactggctcaaggtgtaga gggagcagag acgaagaccc caggaagtca tcctgcaatg ggagagacacgaacaaacca aggaaatcta agtttcgaga gaaaggaggg caacttctac tcttcaacctctactgaaaa cacaaacaac aaagcagaag actcctctct tctgactgtt tacacctttccgtgccggga gcgcacctcg ccgtgtcttg tgttgctgta ataacgacgt agatctgtgcagcgaggtcc accccgttgt tgtccctgca gggcagaaaa acgtctaact tcatgctgtctgtgtgaggc tccctccctc cctgctccct gctcccggct ctgaggctgc cccaggggcactgtgttctc aggcggggat cacgatcctt gtagacgcac ctgctgagaa tccccgtgctcacagtagct tcctagacca tttactttgc ccatattaaa aagccaagtg tcctgcttggtttagctgtg cagaaggtga aatggaggaa accacaaatt catgcaaagt cctttcccgatgcgtggctc ccagcagagg ccgtaaattg agcgttcagt tgacacattg cacacacagtctgttcagag gcattggagg atgggggtcc tggtatgtct caccaggaaa ttctgtttatgttcttgcag cagagagaaa taaaactcct tgaaaccagc tcaggctact gccactcaggcagcctgtgg gtccttgcgg tgtagggaac ggcctgagag gagcgtgtcc tatccccggacgcatgcagg gcccccacag gagcgtgtcc tatccccgga cgcatgcagg gcccccacaggagcatgtcc tatccctgga cgcatgcagg gcccccacag gagcgtgtac taccccagaacgcatgcagg gcccccacag gagcgtgtac taccccagga cgcatgcagg gcccccactggagcgtgtac taccccagga cgcatgcagg gcccccacag gagcgtgtcc tatccccggaccggacgcat gcagggcccc cacaggagcg tgtactaccc caggacgcat gcagggcccccacaggagcg tgtactaccc caggatgcat gcagggcccc cacaggagcg tgtactaccccaggacgcat gcagggcccc catgcaggca gcctgcagac cacactctgc ctggccttgagccgtgacct ccaggaaggg accccactgg aattttattt ctctcaggtg cgtgccacatcaataacaac agtttttatg tttgcgaatg gctttttaaa atcatattta cctgtgaatcaaaacaaatt caagaatgca gtatccgcga gcctgcttgc tgatattgca gtttttgtttacaagaataa ttagcaatac tgagtgaagg atgttggcca aaagctgctt tccatggcacactgccctct gccactgaca ggaaagtgga tgccatagtt tgaattcatg cctcaagtcggtgggcctgc ctacgtgctg cccgagggca ggggccgtgc agggccagtc atggctgtcccctgcaagtg gacgtgggct ccagggactg gagtgtaatg ctcggtggga gccgtcagcctgtgaactgc caggcagctg cagttagcac agaggatggc ttccccattg ccttctggggagggacacag aggacggctt ccccatcgcc ttctggccgc tgcagtcagc acagagagcggcttccccat tgccttctgg ggagggacac agaggacagc ttccccatcg ccttctggctgctgcagtca gcacagagag cggcttcccc atcgccttct ggggaggggc tccgtgtagcaacccaggtg ttgtccgtgt ctgttgacca atctctattc agcatcgtgt gggtccctaagcacaataaa agacatccac aatggaaaaa ctgcaaaaaa aaaaaaaaaa aa SLC6A3NP_001035.1mskskcsvgl mssvvapake pnavgpkeve lilvkeqngv qltsstltnp rqspveaqdrproteingqfnregaag vwkicpilkg vgftvilisl yvgffynvii awalhylfss fttelpwihc(SEQ IDnnswnspncs dahpgdssgd ssglndtfgt tpaacyferg vlhlhqshgi ddlgpprwqlNO: 58)taclvlvivl lyfslwkgvk tsgkvvwita tmpyvvltal llrgvtlpga idgiraylsvdfyrlceasv widaatqvcf slgvgfgvli afssynkftn ncyrdaivtt sinsltsfssetwgkkidfl lsvigfavdl anvwrfpylc ykngggaflv pyllfmviag mplfymelalgfvvfsflgy maqkhsvpig dvakdgpgli fiiypeaiat lplssawavv ffimlltlgidsamggmesv itglidefql Ihrhrelftl fivlatflls lfcvtnggiy vftlldhfaagtsilfgvli eaigvawfyg vgqfsddiqq mtgqrpslyw rlcwklvspc fllfvvvvsivtfrpphyga yifpdwanal gwviatssma mvpiyaaykf cslpgsfrek layaiapekdrelvdrgevr qftlrhwlkv

The foregoing examples are presented for the purpose of illustrating theinvention and should not be construed as imposing any limitation on thescope of the invention. It will readily be apparent that numerousmodifications and alterations may be made to the specific embodiments ofthe invention described above and illustrated in the examples withoutdeparting from the principles underlying the invention. All suchmodifications and alterations are intended to be embraced by thisapplication.

1-20. (canceled)
 21. A method of treating clear cell renal cell carcinoma (ccRCC) in a subject, comprising: obtaining a sample from the subject; screening the sample for the presence of a clear cell renal cell carcinoma (ccRCC) biomarker set, wherein the biomarker set comprises at least two biomarkers selected from the group consisting of ZNF395, SMPDL3A, SLC28A1, SLC6A3, VEGFA, and EGLN3, wherein one of the at least two biomarkers is SMPDL3A or SLC28A1; wherein the biomarkers are proteins, or nucleic acids encoding the same, or variants thereof, and wherein the variants are allelic variants, splice variants, specifies-specific homologs, paralogs, and/or orthologs; identifying a subject as having ccRCC based on the presence of the biomarker set in the sample; and treating the subject identified as having ccRCC with an effective amount of an anti-ccRCC compound and/or treatment.
 22. The method of claim 21, wherein the at least two biomarkers selected from the group consisting of ZNF395, SMPDL3A, SLC28A1, SLC6A3, VEGFA, and EGLN3 comprises at least three biomarkers.
 23. The method of claim 21, wherein the biomarker set consists of ZNF395, SMPDL3A, and SLC28A1.
 24. The method of claim 21, wherein screening the sample for the presence of a clear cell renal cell carcinoma (ccRCC) biomarker set is carried out using one or more molecular biological methods.
 25. The method of claim 24, wherein the one or more molecular biological methods is or are selected from the group consisting of polymerase chain reaction (PCR), quantitative polymerase chain reaction (qPCR), Western Blot, dot blot, mass spectrometry, nucleic acid sequencing, and immunological methods.
 26. The method of claim 21, wherein the presence of the biomarker set is determined based on comparison of the same biomarker set with a control group.
 27. The method of claim 26, wherein the control group comprises one or more samples obtained from disease-free subjects and/or samples from non-diseased areas of the same or different subjects suffering from clear cell renal cell carcinoma.
 28. The method of claim 21, wherein the sample is a solid sample or a fluid sample.
 29. The method of claim 28, wherein the solid sample is solid tumour biopsy, optionally wherein the fluid sample is liquid tumour biopsy, urine sample, blood sample, sputum sample, or cell culture medium.
 30. The method of claim 28, wherein the fluid sample contains exosomes suspected to comprise the biomarker set, optionally wherein the exosomes are detected using quantitative polymerase chain reaction (qPCR).
 31. The method of claim 21, wherein the clear cell renal cell carcinoma (ccRCC) is a recurrent ccRCC.
 32. A method of detecting response of a subject to a systemic treatment, the method comprising: a) obtaining a sample from the subject who is receiving or who has received systemic treatment; b) determining the levels of the biomarker set in the sample, wherein the biomarker set comprises at least two biomarkers selected from the group consisting of ZNF395, SMPDL3A, SLC28A1, SLC6A3, VEGFA, and EGLN3, wherein one of the at least two biomarkers is SMPDL3A or SLC28A1, wherein the biomarkers are proteins, or nucleic acids encoding the same, or variants thereof, and wherein the variants are allelic variants, splice variants, specifies-specific homologs, paralogs, and/or orthologs; wherein an increase in levels or presence of the biomarker set in the sample relative to a sample obtained from the subject prior to receiving said systemic treatment indicates that the subject is not responsive to said systemic treatment; and c) treating the subject identified as not responsive to said systemic treatment with an effective amount of a different systemic treatment.
 33. The method of claim 32, wherein the at least two biomarkers selected from the group consisting of ZNF395, SMPDL3A, SLC28A1, SLC6A3, VEGFA, and EGLN3 comprises at least three biomarkers.
 34. The method of claim 32, wherein the biomarker set consists of ZNF395, SMPDL3A, and SLC28A1.
 35. The method of claim 32, wherein determining the levels of the biomarker set in the sample is carried out using one or more molecular biological methods.
 36. The method of claim 35, wherein the one or more molecular biological methods is or are selected from the group consisting of polymerase chain reaction (PCR), quantitative polymerase chain reaction (qPCR), Western Blot, dot blot, mass spectrometry, nucleic acid sequencing, and immunological methods.
 37. The method of claim 32, wherein the sample is a solid sample or a fluid sample.
 38. The method of claim 37, wherein the solid sample is solid tumour biopsy, optionally wherein the fluid sample is liquid tumour biopsy, urine sample, blood sample, sputum sample, or cell culture medium.
 39. The method of claim 37, wherein the fluid sample contains exosomes suspected to comprise the biomarker set, optionally wherein the exosomes are detected using quantitative polymerase chain reaction (qPCR). 